docs: survey_weight is col 28 under schema v6 (was col 26 in v5)

Rebase onto the v6 main (bd53230) shifted survey_weight from col 26 to
col 28: v5→v6 inserted cog_legacy_state/cog_legacy_county at positions
10-11 (26→28 cols). Position confirmed against the regenerated v6
fixture and both corpus docs (reader-specification.md §3 'Long parquet
schema (28 columns)' row 28; data_dictionary.md '28-column schema v6'
row 28).

.Rbuildignore

@@ -16,4 +16,3 @@
 ^Meta$
 ^\.gitea$
 ^CLAUDE\.md$
-^\.superpowers$

.gitignore

@@ -9,6 +9,3 @@ docs/
 /Meta/
 .DS_Store
 /.quarto/
-
-# SDD working artifacts (ledger, briefs, review packages) — plans/ stays tracked
-.superpowers/sdd/

R/config.R

@@ -21,30 +21,7 @@
   .uscogdata_defaults[[key]]
 }
 
-#' Resolve the corpus URL, guaranteeing the trailing slash the package assumes.
-#'
-#' Every consumer builds locations by CONCATENATION -- `paste0(url,
-#' "manifest.json")` in manifest.R, `paste0(url, e$path)` in mirror.R, and the
-#' parquet glob in views.R -- and mirror.R:104 documents the invariant outright
-#' ('url ends in "/"'). Nothing enforced it, so a URL entered without the slash
-#' failed silently and misleadingly:
-#'
-#'   HTTPS -> ".../downloadmanifest.json"; the host answers with an HTML 404
-#'            page, which lands in the JSON parser as the lexical error
-#'            reported in issue #3 -- pointing the user at "login page / wrong
-#'            share" when the real cause was one missing character.
-#'   local -> ".../corpusdata/long/**/*.parquet" and a DuckDB "No files found".
-#'
-#' Normalizing here fixes every consumer at once, rather than each call site
-#' re-deriving the same invariant. An empty setting is passed through
-#' untouched so manifest.R's "not configured" guard still fires instead of the
-#' value degrading into a bare "/" filesystem root.
-#' @noRd
-.resolve_url <- function() {
-  url <- .cfg("url")
-  if (is.null(url) || !nzchar(url) || grepl("/$", url)) return(url)
-  paste0(url, "/")
-}
+.resolve_url <- function() .cfg("url")
 
 .resolve_cache_dir <- function() {
   v <- .cfg("cache_dir")

R/explain.R

@@ -60,21 +60,6 @@ cog_explain <- function(result, format = c("print", "list")) {
     cli::cli_text("Basis: {prov$basis}{note}")
   }
 
-  if (!is.null(prov$expenditure_concept)) {
-    concept_note <- if (!is.null(prov$expenditure_concept_note) &&
-                         !is.na(prov$expenditure_concept_note)) {
-      sprintf(" (%s)", prov$expenditure_concept_note)
-    } else {
-      ""
-    }
-    cli::cli_text("Concept: {prov$expenditure_concept}{concept_note}")
-    if (isTRUE(prov$expenditure_concept_direct_suppressed)) {
-      cli::cli_alert_warning(
-        "Direct leg unavailable for at least one requested (year, category) -- affected rows report intergovernmental dollars alone, not Direct + IG. See each row's notes."
-      )
-    }
-  }
-
   cli::cli_h2("Codes observed")
   codes <- prov$codes_summed$observed
   if (length(codes) == 0L) {

R/peers.R

@@ -143,10 +143,6 @@ cog_find_peers <- function(target_govid,
 #' @param per_capita Default `TRUE` — peer compare usually normalizes by
 #'   population.
 #' @param adjust_to_year Integer base year for CPI-U conversion or `NULL`.
-#' @param expenditure_concept `"direct"` (default) or `"total"`. Currently only
-#'   `"direct"` is accepted; the `"total"` option exists in [cog_spending()] for
-#'   single-government queries but cannot be used here because combining Total
-#'   across peer sets counts intergovernmental transfers twice.
 #' @return Tibble matching [cog_spending()]'s columns, plus a `role`
 #'   column taking values `"target"`, `"peer"`, `"summary_p25"`,
 #'   `"summary_p50"`, or `"summary_p75"`, `target_rank` (target's rank
@@ -157,13 +153,8 @@ cog_find_peers <- function(target_govid,
 #'   `cohort_year`, and `cohort_govids`.
 #' @export
 cog_peer_compare <- function(target_govid, peers, category, years,
-                             per_capita = TRUE, adjust_to_year = NULL,
-                             expenditure_concept = c("direct", "total")) {
+                             per_capita = TRUE, adjust_to_year = NULL) {
   call <- match.call()
-  expenditure_concept <- match.arg(expenditure_concept)
-  if (identical(expenditure_concept, "total")) {
-    .abort_concept_not_aggregatable("cog_peer_compare")
-  }
   if (!is.character(target_govid) || length(target_govid) != 1L) {
     cli::cli_abort("`target_govid` must be a length-1 character string.")
   }

R/provenance.R

@@ -6,9 +6,6 @@
                               per_capita, adjust_to_year, result, sql,
                               subtype_col, basis = NA_character_,
                               basis_note = NA_character_,
-                              expenditure_concept = "direct",
-                              expenditure_concept_note = NA_character_,
-                              expenditure_concept_direct_suppressed = FALSE,
                               harmonization = NULL, recipe = NULL,
                               suggestions = list()) {
   manifest <- .uscogdata_env$manifest
@@ -54,9 +51,6 @@
     category = category,
     basis = basis,
     basis_note = basis_note,
-    expenditure_concept = expenditure_concept,
-    expenditure_concept_note = expenditure_concept_note,
-    expenditure_concept_direct_suppressed = isTRUE(expenditure_concept_direct_suppressed),
     harmonization = harmonization %||% list(
       applied = FALSE, na_rows_excluded = 0L, na_amount_excluded = 0,
       note = NA_character_

R/rollup.R

@@ -25,12 +25,6 @@
 #'   population from `gov_population_yearly`. Govs with missing population
 #'   are excluded from the result.
 #' @param adjust_to_year Integer base year for CPI-U conversion, or `NULL`.
-#' @param expenditure_concept `"direct"` (default) or `"total"`. Currently only
-#'   `"direct"` is accepted; the `"total"` option exists in [cog_spending()] for
-#'   single-government queries but cannot be used here because combining Total
-#'   across multiple layers of government double-counts intergovernmental
-#'   transfers (a state's payment to a school district is the same dollar the
-#'   district reports as its own Direct spending).
 #' @return Tibble with columns `year`, `layer`, `canonical_govid`, `gov_name`,
 #'   `spend_subtype`, `category`, `amt_nominal`, optional `amt_real` /
 #'   `amt_per_capita_nominal` / `amt_per_capita_real`, optional `pop_source`,
@@ -39,13 +33,8 @@
 #'   and `rollup$included_govids` / `rollup$excluded_govids`.
 #' @export
 cog_geographic_rollup <- function(govids, category, years,
-                                  per_capita = FALSE, adjust_to_year = NULL,
-                                  expenditure_concept = c("direct", "total")) {
+                                  per_capita = FALSE, adjust_to_year = NULL) {
   call <- match.call()
-  expenditure_concept <- match.arg(expenditure_concept)
-  if (identical(expenditure_concept, "total")) {
-    .abort_concept_not_aggregatable("cog_geographic_rollup")
-  }
   .validate_rollup_layers(govids)
 
   govids <- lapply(govids, .coerce_govid_input, arg = "govids[[layer]]")

R/spending.R

@@ -42,34 +42,6 @@
 #'   `basis = "recipe"` with an inert `harmonization` block (`applied =
 #'   FALSE`, pointing at the `recipe` block instead) rather than a
 #'   possibly-misleading `"harmonized"`/`"raw"` value.
-#' @param expenditure_concept `"direct"` (default) returns only the
-#'   government's own direct spending (item codes `E`/`F`/`G`), unchanged
-#'   from prior releases. `"total"` additionally UNIONs in the
-#'   intergovernmental leg -- payments to local governments (`M` codes) and
-#'   to the state government (`L` codes, excluding the `L--` family-total
-#'   rollup) -- so results gain rows with `spend_subtype ==
-#'   "intergovernmental"`. Requires the active corpus's `summary_categories`
-#'   to carry M/L rows (added by cog_pipeline PR #59); aborts with class
-#'   `uscogdata_ig_categories_unsupported` on an older corpus rather than
-#'   silently under-reporting. Mutually exclusive with `recipe` (a recipe
-#'   already defines its own component codes). **Do not sum `"total"`
-#'   results across levels of government** (e.g. state + county + city):
-#'   a state's `M12` payment to a school district is the same dollar the
-#'   district reports as its own direct `E12`, so summing both double-counts
-#'   it. This matters in particular with [cog_geographic_rollup()], which
-#'   sums across exactly that kind of multi-layer government set.
-#'
-#'   In the legacy wide era (<= FY2011), some functions are published ONLY
-#'   as an aggregate-flagged family total (e.g. Corrections' `E04`/`E05`
-#'   split), which the Direct leg excludes by construction but the IG leg
-#'   deliberately keeps (see `inst/sql/24-ig_long.sql`). For a `"total"`
-#'   query, any (year, category) where this leaves intergovernmental rows
-#'   with NO Direct counterpart is flagged: the affected rows' `notes`
-#'   name the harmonization recipe that recovers the missing Direct
-#'   component (when one exists), and
-#'   `provenance$expenditure_concept_direct_suppressed` is `TRUE` -- the
-#'   figure in those rows is the intergovernmental leg alone, not Direct +
-#'   IG.
 #' @return Tibble with columns `year`, `canonical_govid`, `gov_name`,
 #'   `spend_subtype`, `category`, `amt_nominal`, optional `amt_real`,
 #'   optional `amt_per_capita_nominal`, optional `amt_per_capita_real`,
@@ -78,13 +50,12 @@
 #' @export
 cog_spending <- function(govid, years, category = NULL,
                          per_capita = FALSE, adjust_to_year = NULL,
-                         basis = c("harmonized", "raw"), recipe = NULL,
-                         expenditure_concept = c("direct", "total")) {
+                         basis = c("harmonized", "raw"), recipe = NULL) {
   .verb_spendrev(
     verb          = "cog_spending",
     view_base     = "spending_annotated",
     subtype_col   = "spend_subtype",
-    flow_prefixes = c("E", "F", "G"),
+    flow_prefixes = c("E", "F", "G", "K"),
     call          = match.call(),
     govid         = govid,
     years         = years,
@@ -92,79 +63,22 @@ cog_spending <- function(govid, years, category = NULL,
     per_capita    = per_capita,
     adjust_to_year = adjust_to_year,
     basis         = basis,
-    recipe        = recipe,
-    expenditure_concept = expenditure_concept
+    recipe        = recipe
   )
 }
 
-#' @noRd
-.abort_concept_not_aggregatable <- function(verb) {
-  cli::cli_abort(c(
-    "{.code expenditure_concept = \"total\"} cannot be used in {.fn {verb}}.",
-    "*" = "Use {.code expenditure_concept = \"direct\"} (the default) for any \\
-           comparison or sum that spans more than one government.",
-    "i" = "Why: Census \"Total\" is a government's own Direct spending PLUS the \\
-           money it hands to other governments. The receiving government reports \\
-           that same dollar again as its own Direct when it actually spends it, \\
-           so combining Total across governments double-counts intergovernmental \\
-           transfers.",
-    "i" = "For one government's own Total, use \\
-           {.code cog_spending(expenditure_concept = \"total\")}."
-  ), class = "uscogdata_concept_not_aggregatable")
-}
-
 #' @noRd
 .verb_spendrev <- function(verb, view_base, subtype_col, flow_prefixes, call,
                            govid, years, category,
                            per_capita, adjust_to_year,
-                           basis = c("harmonized", "raw"), recipe = NULL,
-                           expenditure_concept = c("direct", "total")) {
+                           basis = c("harmonized", "raw"), recipe = NULL) {
   basis_explicit <- length(basis) == 1L
   basis <- match.arg(basis, c("harmonized", "raw"))
-  # match.arg() itself throws a base `simpleError`, not an rlang-classed
-  # condition; wrap it so an invalid expenditure_concept aborts consistently
-  # with the rest of this package's validation (cli::cli_abort -> rlang_error).
-  expenditure_concept <- tryCatch(
-    match.arg(expenditure_concept, c("direct", "total")),
-    error = function(e) {
-      cli::cli_abort(
-        "`expenditure_concept` must be one of {.val direct} or {.val total}.",
-        class = "uscogdata_invalid_expenditure_concept",
-        parent = e
-      )
-    }
-  )
 
   govid <- .coerce_govid_input(govid, arg = "govid")
   .validate_verb_inputs(govid, years, category, per_capita, adjust_to_year,
                         recipe)
 
-  if (!is.null(recipe) && identical(expenditure_concept, "total")) {
-    cli::cli_abort(c(
-      "`recipe` and `expenditure_concept = \"total\"` are mutually exclusive.",
-      i = "A recipe defines its own component codes; pass one or the other.",
-      i = "For a recipe's intergovernmental counterpart, use the matching IG recipe (e.g. `corrections_ig_local_combined`)."
-    ), class = "uscogdata_recipe_concept_conflict")
-  }
-
-  # .verb_spendrev() is shared with cog_revenue(), which never exposes
-  # expenditure_concept and always resolves it to "direct" -- so nothing on
-  # the public API can reach this today. But it's a cheap guard against a
-  # future call (direct or via a modified cog_revenue()) that would UNION
-  # the IG leg's expenditure M/L rows into a revenue result, which has no
-  # matching IG view and no sensible meaning.
-  if (identical(expenditure_concept, "total") &&
-      !identical(view_base, "spending_annotated")) {
-    cli::cli_abort(
-      paste0(
-        "`expenditure_concept = \"total\"` is only supported for spending ",
-        "(view_base = \"spending_annotated\"); got view_base = ",
-        "{.val {view_base}}."
-      ),
-      class = "uscogdata_expenditure_concept_unsupported"
-    )
-  }
-
   years   <- as.integer(years)
   if (!is.null(adjust_to_year)) adjust_to_year <- as.integer(adjust_to_year)
 
@@ -191,13 +105,7 @@ cog_spending <- function(govid, years, category = NULL,
     category_for_prov <- recipe_label
   } else {
     view <- .select_view(view_base, resolved$basis)
-    ig_view <- if (identical(expenditure_concept, "total")) {
-      .require_ig_categories(con)
-      .select_ig_view(resolved$basis)
-    } else {
-      NULL
-    }
-    sql <- .build_verb_sql(view, subtype_col, govid, years, category, ig_view)
+    sql <- .build_verb_sql(view, subtype_col, govid, years, category)
     result <- tibble::as_tibble(DBI::dbGetQuery(con, sql))
   }
 
@@ -206,6 +114,8 @@ cog_spending <- function(govid, years, category = NULL,
     result <- .attach_real_dollars(result, adjust_to_year, per_capita)
   }
 
+  result$notes <- .notes_column(result)
+
   # A recipe result doesn't go through spending_annotated(_harmonized) /
   # revenue_annotated(_harmonized) at all -- .run_recipe()'s generic join
   # reads `long` directly -- so `basis` and the `harmonization` exclusion
@@ -231,64 +141,7 @@ cog_spending <- function(govid, years, category = NULL,
     harmonization <- .build_harmonization_block(
       con, govid, years, resolved, flow_prefixes
     )
-    # C1(a): gap detection must run against the Direct leg alone. `result`
-    # can also carry UNION'd intergovernmental rows (expenditure_concept =
-    # "total"), and the wide era (<= FY2011) routinely has legacy IG dollars
-    # surviving (ig_long deliberately keeps aggregate rows) for a
-    # (year, category) whose legacy Direct dollars were suppressed (spending_
-    # long/spending_long_harmonized both filter NOT is_aggregate). Passing
-    # the UNION'd result here would let a surviving IG row count as coverage
-    # and silently cancel the recipe-hint suggestion that should fire.
-    direct_leg_result <- if (identical(expenditure_concept, "total")) {
-      result[!(result[[subtype_col]] %in% "intergovernmental"), , drop = FALSE]
-    } else {
-      result
-    }
-    suggestions <- .build_suggestions(con, govid, years, category,
-                                       direct_leg_result,
-                                       resolved$basis, flow_prefixes)
-  }
-
-  # C1(b): when expenditure_concept = "total", flag any row where the IG
-  # leg has dollars but the Direct leg has none for that same (year,
-  # canonical_govid, category) AND a harmonization recipe actually recovers
-  # the missing Direct dollars for that exact triple -- see
-  # .detect_direct_suppressed() for why bare Direct-row absence alone is NOT
-  # sufficient (the dominant real cause is a government that simply has no
-  # direct spending in that category, which is correct, ordinary data). When
-  # a covering recipe is found, both the row-level notes and the provenance
-  # say so rather than pass silently as a plausible Total.
-  direct_suppressed_info <- if (identical(expenditure_concept, "total")) {
-    .detect_direct_suppressed(con, result, subtype_col)
-  } else {
-    list(flag = rep(FALSE, nrow(result)), notes = rep(NA_character_, nrow(result)))
-  }
-  direct_suppressed <- direct_suppressed_info$flag
-  direct_suppressed_flag <- isTRUE(any(direct_suppressed))
-
-  result$notes <- .notes_column(result, direct_suppressed_info$notes)
-
-  # Determine expenditure_concept_note: only non-empty for "total", explains
-  # how the IG leg was assembled from legacy-era aggregates. When the Direct
-  # leg is suppressed for at least one requested (year, category), append an
-  # explicit warning rather than let the base note's "Total = Direct + IG"
-  # framing stand unqualified for rows where that arithmetic didn't happen.
-  expenditure_concept_note_for_prov <- if (identical(expenditure_concept, "total")) {
-    base_note <- "Total = Direct + intergovernmental (M to local govts + L to state govts). Legacy-era IG is assembled from aggregate-flagged rows, which are year-disjoint from their modern leaf components; the L-- family total is excluded."
-    if (direct_suppressed_flag) {
-      paste0(
-        base_note,
-        " NOTE: for at least one requested (year, category) the Direct leg ",
-        "has NO rows in this corpus (a legacy aggregate-only family) -- the ",
-        "affected result rows report the intergovernmental leg alone, not ",
-        "Direct + IG. See `expenditure_concept_direct_suppressed` and each ",
-        "affected row's `notes`."
-      )
-    } else {
-      base_note
-    }
-  } else {
-    NA_character_
+    suggestions <- .build_suggestions(con, govid, years, category, resolved$basis)
   }
 
   prov <- .build_provenance(
@@ -304,9 +157,6 @@ cog_spending <- function(govid, years, category = NULL,
     subtype_col    = subtype_col,
     basis          = basis_for_prov,
     basis_note     = basis_note_for_prov,
-    expenditure_concept = expenditure_concept,
-    expenditure_concept_note = expenditure_concept_note_for_prov,
-    expenditure_concept_direct_suppressed = direct_suppressed_flag,
     harmonization  = harmonization,
     recipe         = recipe_block,
     suggestions    = suggestions
@@ -361,43 +211,6 @@ cog_spending <- function(govid, years, category = NULL,
   if (identical(basis, "harmonized")) paste0(view_base, "_harmonized") else view_base
 }
 
-#' @noRd
-.select_ig_view <- function(basis) {
-  if (identical(basis, "harmonized")) "ig_annotated_harmonized" else "ig_annotated"
-}
-
-#' Abort unless the active corpus's `summary_categories` actually carries
-#' intergovernmental (M/L) rows.
-#'
-#' The 66 M/L category rows arrived via cog_pipeline PR #59 with NO
-#' `schema_version` bump (`DESCRIPTION` still declares `MinCorpusSchema: 4`),
-#' so `schema_version` alone cannot gate `expenditure_concept = "total"` --
-#' a pre-#59 corpus can validly report schema_version 4, 5, or 6 and still
-#' have zero M/L rows in `summary_categories`. Against such a corpus,
-#' `ig_annotated`'s LEFT JOIN to `summary_categories` silently produces NA
-#' `category`/`spend_subtype` for every IG row: with a `category` filter
-#' this returns 0 rows (reads as "no intergovernmental spending" rather than
-#' "can't tell"), and with `category = NULL` every IG dollar collapses into
-#' one NA-subtype group that is invisible to the `spend_subtype ==
-#' "intergovernmental"` filter this package's own tests, roxygen, and
-#' vignette all rely on. Checking the data directly (rather than
-#' schema_version) is the only reliable gate.
-#' @noRd
-.require_ig_categories <- function(con, what = "expenditure_concept = \"total\"") {
-  n <- DBI::dbGetQuery(con,
-    "SELECT COUNT(*) AS n FROM summary_categories WHERE LEFT(item_code, 1) IN ('M', 'L')"
-  )$n
-  if (identical(as.integer(n), 0L)) {
-    cli::cli_abort(c(
-      sprintf("%s requires a corpus with intergovernmental category rows.", what),
-      x = "The active corpus's `summary_categories` has no M/L (intergovernmental) rows.",
-      i = "This corpus predates the intergovernmental category rows added by cog_pipeline PR #59.",
-      i = "Point USCOGDATA_URL at a newer corpus that includes the M/L summary_categories rows."
-    ), class = "uscogdata_ig_categories_unsupported")
-  }
-  invisible(TRUE)
-}
-
 #' @noRd
 .sql_lit_chr <- function(x) {
   safe <- gsub("'", "''", x, fixed = TRUE)
@@ -405,8 +218,7 @@ cog_spending <- function(govid, years, category = NULL,
 }
 
 #' @noRd
-.build_verb_sql <- function(view, subtype_col, govid, years, category,
-                            ig_view = NULL) {
+.build_verb_sql <- function(view, subtype_col, govid, years, category) {
   govid_lit <- .sql_lit_chr(govid)
   years_lit <- paste(as.integer(years), collapse = ",")
   category_pred <- if (is.null(category)) {
@@ -415,26 +227,6 @@ cog_spending <- function(govid, years, category = NULL,
     sprintf("AND category IN (%s)", .sql_lit_chr(category))
   }
 
-  # expenditure_concept = "total" adds the intergovernmental leg. UNION ALL,
-  # never UNION: the two legs are disjoint by item_code prefix (E/F/G vs M/L),
-  # so de-duplication would be pure cost, and a silent row-drop if two
-  # governments ever reported identical values.
-  source_expr <- if (is.null(ig_view)) {
-    view
-  } else {
-    sprintf("(SELECT * FROM %s UNION ALL SELECT * FROM %s)", view, ig_view)
-  }
-
-  # bool_or(), not bool_and(): a no-op for the Direct/revenue legs (those
-  # views filter NOT is_aggregate, so no row in any group is ever aggregate),
-  # but load-bearing for the IG leg, which deliberately keeps aggregate rows
-  # (see inst/sql/24-ig_long.sql). The wide era is dense -- every government
-  # has a row for every code in a family, most of them $0 -- so a $0 leaf
-  # commonly lands in the same (year, gov, subtype, category) group as the
-  # real aggregate row. bool_and() would then read FALSE for that group even
-  # though its dollars came entirely from an aggregate row, silently
-  # suppressing the "Aggregate fallback applied" note on exactly the rows
-  # this feature exists to surface.
   sprintf(
     "SELECT
        year,
@@ -444,14 +236,14 @@ cog_spending <- function(govid, years, category = NULL,
        category,
        SUM(amt) * 1000.0 AS amt_nominal,
        string_agg(DISTINCT item_code, ',' ORDER BY item_code) AS codes_included,
-       bool_or(is_aggregate) AS aggregate_fallback
+       bool_and(is_aggregate) AS aggregate_fallback
      FROM %2$s
      WHERE canonical_govid IN (%3$s)
        AND year IN (%4$s)
        %5$s
      GROUP BY year, canonical_govid, gov_name, xwalk_gov_name, %1$s, category
      ORDER BY year, canonical_govid, %1$s, category",
-    subtype_col, source_expr, govid_lit, years_lit, category_pred
+    subtype_col, view, govid_lit, years_lit, category_pred
   )
 }
 
@@ -504,131 +296,11 @@ cog_spending <- function(govid, years, category = NULL,
   result
 }
 
-#' Detect rows where expenditure_concept = "total" is reporting the
-#' intergovernmental leg with NO Direct counterpart in the same (year,
-#' canonical_govid, category) group AND a harmonization recipe actually
-#' recovers the missing Direct dollars for that exact (year, canonical_govid,
-#' category) triple.
-#'
-#' Bare Direct-row absence is deliberately NOT sufficient on its own: the
-#' dominant real cause of "no Direct sibling row" is a government that simply
-#' has no direct spending in that category (e.g. a state that funds K-12
-#' entirely through school districts), which is correct, ordinary data, not
-#' suppression. Genuine suppression -- a legacy aggregate-only family whose
-#' Direct-leg basis query excludes it by construction (spending_long/
-#' spending_long_harmonized both filter NOT is_aggregate) -- always has a
-#' covering harmonization recipe, because that is exactly what the recipe
-#' catalog exists to recover (see R/suggestions.R and `cog_recipes()`). So
-#' checking "does a recipe actually cover this triple" cleanly separates the
-#' two cases instead of conflating them.
-#'
-#' Returns `list(flag, notes)`, both the same length as `result`: `flag` is
-#' `TRUE` only for the `spend_subtype == "intergovernmental"` row(s) in a
-#' suppressed group, and `notes` names the recovering recipe(s) for those
-#' rows (`NA` everywhere else).
 #' @noRd
-.detect_direct_suppressed <- function(con, result, subtype_col) {
-  n <- nrow(result)
-  empty_notes <- rep(NA_character_, n)
-  if (n == 0L) return(list(flag = logical(0), notes = character(0)))
-  is_ig <- result[[subtype_col]] %in% "intergovernmental"
-  if (!any(is_ig)) return(list(flag = rep(FALSE, n), notes = empty_notes))
-
-  key <- paste(result$year, result$canonical_govid, result$category, sep = "\r")
-  has_direct <- key %in% unique(key[!is_ig])
-  candidate <- is_ig & !has_direct
-
-  flag <- rep(FALSE, n)
-  notes <- empty_notes
-  if (!any(candidate)) return(list(flag = flag, notes = notes))
-
-  idx <- which(candidate)
-  rows <- unique(result[idx, c("year", "canonical_govid", "category")])
-  covering <- .covering_recipes(con, rows)
-  cov_key <- paste(covering$year, covering$canonical_govid, covering$category,
-                    sep = "\r")
-
-  for (i in idx) {
-    k <- paste(result$year[i], result$canonical_govid[i], result$category[i],
-               sep = "\r")
-    m <- match(k, cov_key)
-    if (is.na(m)) next
-    ids <- covering$recipe_ids[[m]]
-    if (length(ids) == 0L) next
-    flag[i] <- TRUE
-    notes[i] <- sprintf(
-      "Direct component is unavailable through this basis for this year; recover it via recipe = '%s' (see cog_recipes()).",
-      paste(sort(unique(ids)), collapse = "', '")
-    )
-  }
-  list(flag = flag, notes = notes)
-}
-
-#' For each (year, canonical_govid, category) triple potentially affected by
-#' a suppressed Direct leg, find the harmonization recipe(s) that (a) cover
-#' this `category` (share a component item_code via `summary_categories`,
-#' excluding any recipe that is itself entirely intergovernmental M/L -- the
-#' same exclusion `.build_suggestions()` applies, see I2) and (b) actually
-#' produce a `long` row for this exact (canonical_govid, year) via the same
-#' generic join `.run_recipe()` uses (component year_min/year_max +
-#' gov_type_scope, no is_aggregate filter -- a recipe's whole point is to
-#' recover data that's aggregate-only). Adds a list-column `recipe_ids`
-#' (possibly length-0) to `rows`.
-#' @noRd
-.covering_recipes <- function(con, rows) {
-  rows$recipe_ids <- vector("list", nrow(rows))
-  cats <- unique(rows$category[!is.na(rows$category)])
-  if (length(cats) == 0L) return(rows)
-
-  cand <- DBI::dbGetQuery(con, sprintf(
-    "SELECT DISTINCT sc.category, r.recipe_id
-     FROM harmonization_recipes r
-     JOIN summary_categories sc ON sc.item_code = r.component_code
-     WHERE sc.category IN (%s)
-       AND r.recipe_id NOT IN (
-         SELECT DISTINCT recipe_id FROM harmonization_recipes
-         WHERE LEFT(component_code, 1) IN ('M', 'L')
-       )",
-    .sql_lit_chr(cats)
-  ))
-  if (nrow(cand) == 0L) return(rows)
-
-  recipe_ids_all <- unique(cand$recipe_id)
-  govids <- unique(rows$canonical_govid)
-  years  <- unique(rows$year)
-  covered <- DBI::dbGetQuery(con, sprintf(
-    "SELECT DISTINCT r.recipe_id, l.canonical_govid, l.year
-     FROM long l
-     JOIN harmonization_recipes r
-       ON l.item_code = r.component_code
-      AND l.year BETWEEN r.year_min AND r.year_max
-      AND (r.gov_type_scope = 'all'
-           OR (r.gov_type_scope = 'state' AND l.type = 0)
-           OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
-     WHERE r.recipe_id IN (%s)
-       AND l.canonical_govid IN (%s)
-       AND l.year IN (%s)",
-    .sql_lit_chr(recipe_ids_all), .sql_lit_chr(govids), paste(years, collapse = ",")
-  ))
-
-  for (i in seq_len(nrow(rows))) {
-    cat_i <- rows$category[i]
-    if (is.na(cat_i)) next
-    cat_recipe_ids <- cand$recipe_id[cand$category == cat_i]
-    if (length(cat_recipe_ids) == 0L) next
-    sub <- covered[covered$canonical_govid == rows$canonical_govid[i] &
-                   covered$year == rows$year[i] &
-                   covered$recipe_id %in% cat_recipe_ids, ]
-    rows$recipe_ids[[i]] <- sort(unique(sub$recipe_id))
-  }
-  rows
-}
-
-#' @noRd
-.notes_column <- function(result, direct_suppressed_notes = NULL) {
+.notes_column <- function(result) {
   n <- nrow(result)
   if (n == 0L) return(character(0))
-  parts <- vector("list", 3L)
+  parts <- vector("list", 2L)
   agg <- result[["aggregate_fallback"]]
   parts[[1]] <- if (!is.null(agg)) {
     ifelse(agg %in% TRUE,
@@ -645,11 +317,6 @@ cog_spending <- function(govid, years, category = NULL,
   } else {
     rep(NA_character_, n)
   }
-  parts[[3]] <- if (!is.null(direct_suppressed_notes)) {
-    direct_suppressed_notes
-  } else {
-    rep(NA_character_, n)
-  }
   out <- character(n)
   for (i in seq_len(n)) {
     pieces <- vapply(parts, `[[`, character(1), i)

R/suggestions.R

@@ -1,8 +1,9 @@
 # R/suggestions.R
 # Recipe-component-driven signposting: when a basis = "harmonized" query for
-# a category comes back with a coverage gap in some requested years (the
-# result has no rows at all in that year) that a harmonization recipe would
-# actually fill for this government, surface that recipe as a suggestion.
+# a category asks for a code that is itself a harmonization recipe
+# component, and that specific code has no rows in some requested years
+# while the recipe's own generic join would still fill those years for this
+# government, surface that recipe as a suggestion.
 #
 # This is deliberately keyed off the recipe catalog's component codes, not
 # off harmonization_map rows: no live map row carries a non-blank
@@ -12,83 +13,58 @@
 # suggestion off of, just a leaf-code absence a recipe happens to fill).
 # See docs/phase_r_harmonization_review.md § 0.3.
 #
-# Scope is deliberately narrow: signposting only runs when the caller
+# Scope is deliberately narrow in one respect and, as of Phase R3 Task 19c,
+# deliberately WIDE in another: signposting only runs when the caller
 # supplied a `category` (an un-scoped, all-categories query has no single
-# coverage question to answer) and only flags a recipe when the ACTUAL
-# result has zero rows in a requested year AND the candidate recipe's own
-# generic join (same join .run_recipe() uses, including its wide-era
-# aggregate rows) produces at least one row for this government in that
-# year. Checking presence per-government (not corpus-wide) avoids false
-# positives from ordinary reporting variance -- most governments don't use
-# every sibling code in a multi-code category every year, and that is not
-# a format-boundary gap worth signposting.
-#
-# C1(a): for expenditure_concept = "total" callers, `result` here must
-# already be the Direct-leg subset (the caller filters out
-# spend_subtype == "intergovernmental" rows before calling in). A gap year
-# is "the requested year has no Direct rows", never "no rows at all" --
-# an IG row surviving on a legacy aggregate that Direct excludes must not
-# read as coverage and cancel the very suggestion that would recover it.
+# coverage question to answer), but within that category it now checks
+# EACH recipe component that is itself a category member individually,
+# rather than asking whether the whole category *result* has zero rows
+# that year. A recipe fires when one of its own components has zero rows
+# for this government in a requested year, AND SOME OTHER component of that
+# SAME recipe -- excluding the gapped one itself -- has a row (same join
+# .run_recipe() uses, aggregate rows included) for that year. This is the
+# literal review-doc § 0.3 criterion: "...has no rows ... but other
+# components do." A component's OWN aggregate-only row does not satisfy
+# its own gap (self-coverage is not "other components"); only a genuinely
+# different sibling component can. This fires even if OTHER, unrelated
+# codes in the same category have full data that year and the overall
+# result looks complete. That is a deliberate narrowing of the R2-era
+# false-positive guard: most governments don't use every sibling code in a
+# multi-code category every year, and per-code detection WILL flag some of
+# that as a "gap" even though it's really just a government not having
+# that particular sub-type of spending, not a format-boundary artifact.
+# The remaining guard against ordinary reporting variance is the
+# per-government, per-OTHER-component `covered` check below (a component
+# is only flagged when a DIFFERENT component of the SAME recipe -- not
+# some unrelated code, and not the gapped component's own aggregate row --
+# actually has something to offer in that year); it no longer tries to
+# avoid noise from sibling *codes*, only from a recipe with genuinely
+# nothing else to contribute. The acceptable noise level this trade
+# produces is a product decision, measured (not tuned here) by
+# data-raw/measure_signposting_rate.R and ruled on at Checkpoint R3.
 
-#' Build the `prov$suggestions` list for a (non-recipe) basis = "harmonized"
-#' verb call: recipes whose generic join would fill a real gap in `result`.
-#'
-#' @param con Active DuckDB connection.
-#' @param govid Character vector of canonical_govid values (the verb's raw
-#'   `govid`).
-#' @param years Integer vector of requested years.
-#' @param category `category` argument as passed to the verb (character
-#'   vector or `NULL`; suggestions are only computed when non-NULL).
-#' @param result The verb's already-computed result tibble (post basis
-#'   query, pre per_capita/adjust_to_year), pre-filtered to the Direct leg
-#'   only when the caller's `expenditure_concept = "total"` (see C1(a)).
-#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
-#' @param flow_prefixes The calling verb's own flow-type prefixes (e.g.
-#'   `c("E", "F", "G")` for `cog_spending()`, `c("T", "A", "U", "B", "C",
-#'   "D")` for `cog_revenue()` -- see `.verb_spendrev()`). Passed through to
-#'   `.attach_ig_counterparts()` to keep the intergovernmental-counterpart
-#'   lookup scoped to the calling verb's own flow family.
-#' @return List of `list(recipe_id, label, available_years, hint,
-#'   ig_recipe_id)`, possibly empty.
+#' Recipe components that are classified under the requested category --
+#' the codes a category-scoped query actually "requests". A recipe can
+#' have components outside the category (e.g. general_gov_e89_wide's E85
+#' leg has no category assignment); those never trigger on their own, they
+#' just were never part of what this query asked for.
 #' @noRd
-.build_suggestions <- function(con, govid, years, category, result, basis,
-                                flow_prefixes) {
-  if (!identical(basis, "harmonized") || is.null(category)) return(list())
-
-  # Exclude any recipe that is ITSELF an intergovernmental (M/L) recipe --
-  # i.e. every one of its own component codes is M/L-prefixed. Without this,
-  # a category whose summary_categories rows span both a Direct family
-  # (e.g. E04/E05, "Corrections") and its M/L counterpart (M04/M05, same
-  # category since Task 1) makes the M/L recipe itself (e.g.
-  # `corrections_ig_local_combined`) a raw top-level candidate for a plain
-  # (Direct) cog_spending() call -- following that hint would silently
-  # return intergovernmental dollars under `expenditure_concept = "direct"`
-  # provenance. This is a stronger, unconditional exclusion than the
-  # flow-prefix gate below/in `.attach_ig_counterparts()`: an M/L recipe
-  # should never be suggested as a coverage-gap filler for EITHER verb, not
-  # just kept from being named as the *counterpart* of another suggestion.
-  candidates <- DBI::dbGetQuery(con, sprintf(
-    "SELECT DISTINCT recipe_id FROM harmonization_recipes
-     WHERE component_code IN (
-       SELECT DISTINCT item_code FROM summary_categories WHERE category IN (%s)
-     )
-     AND recipe_id NOT IN (
-       SELECT DISTINCT recipe_id FROM harmonization_recipes
-       WHERE LEFT(component_code, 1) IN ('M', 'L')
-     )",
+.category_recipe_components <- function(con, category) {
+  DBI::dbGetQuery(con, sprintf(
+    "SELECT DISTINCT r.recipe_id, r.component_code, r.year_min, r.year_max,
+            r.gov_type_scope
+     FROM harmonization_recipes r
+     JOIN summary_categories sc
+       ON sc.item_code = r.component_code AND sc.category IN (%s)",
     .sql_lit_chr(category)
-  ))$recipe_id
-  if (length(candidates) == 0L) return(list())
+  ))
+}
 
-  result_years <- if (is.null(result) || nrow(result) == 0L) {
-    integer(0)
-  } else {
-    unique(as.integer(result$year))
-  }
-  gap_years <- setdiff(as.integer(years), result_years)
-  if (length(gap_years) == 0L) return(list())
-
-  meta <- tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
+#' Label + overall year coverage for a set of recipe ids (the suggestion's
+#' `label`/`available_years`).
+#' @noRd
+.recipe_meta <- function(con, candidates) {
+  tibble::as_tibble(DBI::dbGetQuery(con, sprintf(
     "SELECT recipe_id, any_value(label) AS label,
             MIN(year_min) AS year_min, MAX(year_max) AS year_max
      FROM harmonization_recipes
@@ -96,13 +72,48 @@
      GROUP BY recipe_id",
     .sql_lit_chr(candidates)
   )))
+}
 
-  # Which (recipe_id, year) pairs the recipe's own generic join actually
-  # covers for this government, restricted to the gap years -- the same
-  # join .run_recipe() uses (component year_min/year_max + gov_type_scope,
-  # no is_aggregate filter), just checking existence instead of summing.
-  covered <- DBI::dbGetQuery(con, sprintf(
-    "SELECT DISTINCT r.recipe_id, l.year
+#' Which (recipe_id, component_code, year) triples have at least one
+#' NOT-aggregate row for these governments -- i.e. that specific requested
+#' code itself has data, scoped exactly like .run_recipe()'s join
+#' (component year_min/year_max + gov_type_scope). NOT-aggregate mirrors
+#' what basis = "harmonized" itself excludes: an aggregate-only year is a
+#' gap for that code exactly as it would be in a plain category query.
+#' @noRd
+.component_presence <- function(con, candidates, govid, years_lit) {
+  DBI::dbGetQuery(con, sprintf(
+    "SELECT DISTINCT r.recipe_id, r.component_code, l.year
+     FROM long l
+     JOIN harmonization_recipes r
+       ON l.item_code = r.component_code
+      AND l.year BETWEEN r.year_min AND r.year_max
+      AND (r.gov_type_scope = 'all'
+           OR (r.gov_type_scope = 'state' AND l.type = 0)
+           OR (r.gov_type_scope = 'local' AND l.type BETWEEN 1 AND 3))
+     WHERE NOT l.is_aggregate
+       AND r.recipe_id IN (%s)
+       AND l.canonical_govid IN (%s)
+       AND l.year IN (%s)",
+    .sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
+  ))
+}
+
+#' Which (recipe_id, component_code, year) triples have at least one row
+#' (aggregate rows included) for these governments -- the same scoping
+#' .run_recipe()'s join uses (component year_min/year_max + gov_type_scope),
+#' just checking existence instead of summing. Kept at per-component grain
+#' (not unioned across the whole recipe, unlike the R2/R3-pre-fix version of
+#' this function) so a gap check can require the covering evidence to come
+#' from a DIFFERENT component -- review-doc § 0.3's "other components", not
+#' the gapped component's own aggregate row. This is the per-government
+#' guard against ordinary reporting variance: a recipe with genuinely
+#' nothing to offer from any OTHER component (aggregate or leaf) never
+#' fires.
+#' @noRd
+.recipe_coverage <- function(con, candidates, govid, years_lit) {
+  DBI::dbGetQuery(con, sprintf(
+    "SELECT DISTINCT r.recipe_id, r.component_code, l.year
      FROM long l
      JOIN harmonization_recipes r
        ON l.item_code = r.component_code
@@ -113,13 +124,68 @@
      WHERE r.recipe_id IN (%s)
        AND l.canonical_govid IN (%s)
        AND l.year IN (%s)",
-    .sql_lit_chr(candidates), .sql_lit_chr(govid),
-    paste(gap_years, collapse = ",")
+    .sql_lit_chr(candidates), .sql_lit_chr(govid), years_lit
   ))
+}
+
+#' TRUE if recipe `rid` has at least one requested component with an
+#' in-scope requested year that has no data (`present`), in a year some
+#' OTHER component of the same recipe is otherwise fillable (`covered`,
+#' excluding the component under test) -- the per-code gap the R2
+#' whole-result check couldn't see, covered by another component the way
+#' review-doc § 0.3 specifies (not by the gapped component's own aggregate
+#' row -- that is self-coverage, not "other components", and must not
+#' count).
+#' @noRd
+.recipe_component_gapped <- function(rid, requested, present, covered, years) {
+  comps <- requested[requested$recipe_id == rid, , drop = FALSE]
+  for (i in seq_len(nrow(comps))) {
+    this_code <- comps$component_code[i]
+    in_scope <- years[years >= comps$year_min[i] & years <= comps$year_max[i]]
+    if (length(in_scope) == 0L) next
+    has_data <- present$year[
+      present$recipe_id == rid & present$component_code == this_code
+    ]
+    gap_years <- setdiff(in_scope, has_data)
+    if (length(gap_years) == 0L) next
+    other_covered_years <- covered$year[
+      covered$recipe_id == rid & covered$component_code != this_code
+    ]
+    if (any(gap_years %in% other_covered_years)) return(TRUE)
+  }
+  FALSE
+}
+
+#' Build the `prov$suggestions` list for a (non-recipe) basis = "harmonized"
+#' verb call: recipes whose generic join would fill a real per-code gap for
+#' the requested category.
+#'
+#' @param con Active DuckDB connection.
+#' @param govid Character vector of canonical_govid values (the verb's raw
+#'   `govid`).
+#' @param years Integer vector of requested years.
+#' @param category `category` argument as passed to the verb (character
+#'   vector or `NULL`; suggestions are only computed when non-NULL).
+#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
+#' @return List of `list(recipe_id, label, available_years, hint)`, possibly
+#'   empty.
+#' @noRd
+.build_suggestions <- function(con, govid, years, category, basis) {
+  if (!identical(basis, "harmonized") || is.null(category)) return(list())
+
+  requested <- .category_recipe_components(con, category)
+  if (nrow(requested) == 0L) return(list())
+  candidates <- unique(requested$recipe_id)
+  years_int  <- as.integer(years)
+  years_lit  <- paste(years_int, collapse = ",")
+
+  meta    <- .recipe_meta(con, candidates)
+  present <- .component_presence(con, candidates, govid, years_lit)
+  covered <- .recipe_coverage(con, candidates, govid, years_lit)
 
   suggestions <- list()
   for (rid in candidates) {
-    if (!rid %in% covered$recipe_id) next
+    if (!.recipe_component_gapped(rid, requested, present, covered, years_int)) next
     m <- meta[meta$recipe_id == rid, ]
     suggestions[[length(suggestions) + 1L]] <- list(
       recipe_id = rid,
@@ -128,121 +194,19 @@
       hint = sprintf("re-run with recipe = '%s'", rid)
     )
   }
-  .attach_ig_counterparts(con, suggestions, flow_prefixes)
-}
-
-#' Attach `ig_recipe_id` to each suggestion: the intergovernmental-expenditure
-#' recipe (an M-to-local or L-to-state recipe) whose component codes cover
-#' exactly the same set of function suffixes as the firing recipe's own
-#' components, e.g. `corrections_combined`'s {E04, E05} -> suffixes {"04",
-#' "05"} matches `corrections_ig_local_combined`'s {M04, M05} -> the same
-#' {"04", "05"}. `NULL` when no such recipe exists, which also covers the
-#' case where the firing recipe already IS the IG recipe (self-matches are
-#' excluded, so an IG recipe never names itself as its own counterpart).
-#'
-#' Matching is deliberately an exact set match, not "any suffix in common":
-#' the two-digit suffix only means the same "function" across recipes that
-#' share the underlying Census functional-classification scheme (E/F/G/L/M
-#' all use "04"/"05" for corrections). M/L "combined other" codes (47/89/
-#' 91-94) reuse digits for an unrelated catch-all construct, so e.g.
-#' `general_gov_e89_wide`'s {E85, E89} -> {"85", "89"} must NOT match
-#' `ige_local_m89_wide`'s {"89", "91", "92", "93"} on the shared "89" alone.
-#' Checked by hand against the full harmonization_recipes catalog: only the
-#' corrections family (E/F/G/M, suffixes 04/05) has an exact-set match in
-#' this corpus.
-#'
-#' Exact-set suffix matching is NOT enough on its own, though: the same
-#' reused-digit problem exists ACROSS the revenue-side IG families too.
-#' `ig_local_d47_wide` (D47/D94, suffixes {"47","94"}) is an exact-set match
-#' for `ige_local_m47_wide` (M47/M94, same suffixes) even though one is
-#' intergovernmental REVENUE received from local governments and the other is
-#' intergovernmental EXPENDITURE paid to local governments -- unrelated flows
-#' that happen to reuse "47"/"94" for their own "transit/utilities" and
-#' "other/combined" catch-alls. `ig_federal_b47_wide`, `ig_state_c47_wide`,
-#' and their `*_89` siblings all collide the same way. None of this is
-#' reachable via `cog_revenue()` in the bundled fixture today (its B/C/D
-#' recipes never happen to have a covered gap year for any fixture govid),
-#' but it IS reachable via a mis-scoped `cog_spending()` call on a
-#' revenue-only category, e.g. `cog_spending(gov, category = "IG Federal")`
-#' fires `ig_federal_b47_wide`/`ig_federal_b89_wide` for real in the fixture
-#' -- so this is a live, not merely theoretical, gap.
-#'
-#' Two flow-family checks close this, both required (see
-#' `tests/testthat/test-expenditure-concept.R`, "revenue-flavored ... never
-#' receives an M/L counterpart" tests, for the pairwise verification):
-#'   1. `own_prefix %in% flow_prefixes`: the firing recipe's own component
-#'      codes must belong to the calling verb's own flow family (the same
-#'      `flow_prefixes` `.build_harmonization_block()` uses, see
-#'      `R/basis.R`). This blocks a recipe surfaced through a mis-scoped
-#'      category from ever reaching the M/L search, e.g. `cog_spending()`'s
-#'      flow_prefixes are `c("E","F","G")`, which `ig_federal_b47_wide`'s own
-#'      `"B"` is not part of.
-#'   2. `own_prefix %in% c("E","F","G")`: M/L only ever pairs with the
-#'      DIRECT-expenditure family, never with revenue (`cog_revenue()`'s
-#'      flow_prefixes already fold B/C/D in as ordinary revenue -- there is
-#'      no separate "Total" bolt-on for revenue the way `expenditure_concept`
-#'      adds one for spending) and never with ANOTHER M/L recipe (without
-#'      this check, `ige_local_m47_wide` would wrongly match sibling
-#'      `ige_state_l47_wide` on their shared {"47","94"} suffix set).
-#'      Condition 1 alone does not catch this: under `cog_revenue()`,
-#'      `ig_federal_b47_wide`'s own `"B"` IS inside revenue's own
-#'      `flow_prefixes`, so only this second, family-specific check blocks
-#'      the search.
-#' @noRd
-.attach_ig_counterparts <- function(con, suggestions, flow_prefixes) {
-  if (length(suggestions) == 0L) return(suggestions)
-
-  comp <- DBI::dbGetQuery(con,
-    "SELECT recipe_id, component_code FROM harmonization_recipes")
-  comp$prefix <- substr(comp$component_code, 1L, 1L)
-  comp$suffix <- substr(comp$component_code, 2L, nchar(comp$component_code))
-  suffix_sets <- lapply(split(comp$suffix, comp$recipe_id), function(x) sort(unique(x)))
-  prefix_sets <- lapply(split(comp$prefix, comp$recipe_id), function(x) sort(unique(x)))
-
-  ig_recipe_ids <- unique(comp$recipe_id[comp$prefix %in% c("M", "L")])
-
-  find_counterpart <- function(rid) {
-    own_prefix <- prefix_sets[[rid]]
-    own_suffix <- suffix_sets[[rid]]
-    if (is.null(own_prefix) || is.null(own_suffix)) return(NULL)
-    if (!all(own_prefix %in% flow_prefixes)) return(NULL)
-    if (!all(own_prefix %in% c("E", "F", "G"))) return(NULL)
-    for (cand in ig_recipe_ids) {
-      if (identical(cand, rid)) next
-      if (setequal(suffix_sets[[cand]], own_suffix)) return(cand)
-    }
-    NULL
-  }
-
-  lapply(suggestions, function(s) {
-    # `s$ig_recipe_id <- NULL` would DELETE the element rather than set it
-    # (standard R list-assignment gotcha), leaving no-match entries missing
-    # the key entirely instead of carrying it as NULL. Single-bracket
-    # assignment with a wrapped list preserves a NULL-valued element so the
-    # field is always present, per the brief's "NULL when there is none".
-    s["ig_recipe_id"] <- list(find_counterpart(s$recipe_id))
-    s
-  })
+  suggestions
 }
 
 #' Emit the single cli::cli_inform() message summarizing all suggestions
 #' for a verb call (the brief's "one message", not one per suggestion).
 #' Bullet text is pre-formatted plain text (no cli/glue `{}` markup) since
 #' recipe ids/labels are untrusted-ish data values, not literal call-site
-#' expressions. When a suggestion has an `ig_recipe_id`, one indented
-#' continuation line is appended naming the intergovernmental counterpart
-#' recipe (embedded `\n` renders as a hanging-indent continuation of the
-#' same bullet under cli, not a new bullet).
+#' expressions.
 #' @noRd
 .inform_suggestions <- function(suggestions) {
   bullets <- vapply(suggestions, function(s) {
-    bullet <- sprintf("%s (%d-%d): %s", s$recipe_id,
+    sprintf("%s (%d-%d): %s", s$recipe_id,
             s$available_years[1], s$available_years[2], s$hint)
-    if (!is.null(s$ig_recipe_id)) {
-      bullet <- paste0(bullet, sprintf(
-        "\n  intergovernmental counterpart: recipe = '%s'", s$ig_recipe_id))
-    }
-    bullet
   }, character(1))
   cli::cli_inform(c(
     i = "Coverage gap detected for the requested years; a harmonization recipe may fill it:",

R/views.R

@@ -1,35 +1,23 @@
 # R/views.R
 
-# SQL files that cannot be registered unconditionally against a v4 corpus,
-# for one of two distinct reasons -- both fail at CREATE VIEW time (DuckDB
-# resolves a view's source schema eagerly, even though it defers execution),
-# so a v4 corpus can't tolerate either unconditionally:
-#
-#  (a) Missing FILE. 33-/34-/35- read_parquet() a v5-only parquet table
+# SQL files whose view definitions read schema-v5-only parquet tables
 # (harmonization_map.parquet, harmonization_recipes.parquet,
-#      series_breaks.parquet) that doesn't exist at all on a v4 corpus --
-#      "IO Error: No files found".
-#
-#  (b) Missing COLUMN. 22-/23-/25- reference `long.harmonized_code`, a
-#      column that does not exist on a v4 corpus's `long` table (harmonized
-#      space was introduced in schema v5) -- "Binder Error: Referenced
-#      column harmonized_code not found". 42-/43-/45- are on this list only
-#      because they SELECT s.* FROM the (a)/(b) views above, so they'd fail
-#      to resolve their own source view if it weren't already skipped.
-#
-# Registration is therefore gated on manifest$schema_version >= 5 for all of
-# them; verb-level *usage* of the resulting views is separately gated by
-# .resolve_basis() / .require_schema_v5().
+# series_breaks.parquet) or select from views built on top of them. DuckDB's
+# read_parquet() resolves the file at CREATE VIEW time (even for a view, it
+# still needs the source schema) and errors immediately -- "IO Error: No
+# files found" -- if the path doesn't exist, so these cannot be registered
+# unconditionally against a v4 corpus the way the rest of inst/sql/ is.
+# Registration is therefore gated on manifest$schema_version >= 5; verb-level
+# *usage* of the resulting views is separately gated by .resolve_basis() /
+# .require_schema_v5().
 .harmonization_view_files <- c(
   "22-spending_long_harmonized.sql",
   "23-revenue_long_harmonized.sql",
-  "25-ig_long_harmonized.sql",
   "33-harmonization_map.sql",
   "34-harmonization_recipes.sql",
   "35-series_breaks_pq.sql",
   "42-spending_annotated_harmonized.sql",
-  "43-revenue_annotated_harmonized.sql",
-  "45-ig_annotated_harmonized.sql"
+  "43-revenue_annotated_harmonized.sql"
 )
 
 #' Register DuckDB views from inst/sql/ SQL files

README.md

@@ -25,32 +25,30 @@ package implements.
 - `USCOGDATA_CACHE_DIR` — optional override for the manifest cache directory
 - `USCOGDATA_MANIFEST_TTL_SECS` — optional manifest re-fetch TTL (default 3600)
 
-## Direct vs Total spending
+## Raw-parquet caveat: `survey_weight` is not an aggregation weight
 
-`cog_spending(..., expenditure_concept = c("direct", "total"))` controls
-whose spending a result counts. `"direct"` (the default) is a government's
-own current operations, capital outlay, and other direct spending. `"total"`
-additionally adds in the intergovernmental legs — money it hands to other
-governments to spend on its behalf — which is meaningful for describing one
-government's own budget over time, but double-counts when summed across
-governments (a state's payment to a county is the same dollar the county
-reports as its own direct spending).
-
-**Rule of thumb: any figure that spans more than one government uses
-`direct`.** `cog_geographic_rollup()` and `cog_peer_compare()` enforce this
-by refusing `expenditure_concept = "total"`. See
-`vignette("total-spending", package = "uscogdata")` for the full
-explanation with worked examples.
+Users reading the corpus parquet directly (DuckDB, arrow) will see a
+`survey_weight` column (schema v6, col 28). It is legacy Census IndFin
+sample-design **metadata passed through verbatim** — the Census Bureau's own
+source documentation says it "is for informational purposes only and should
+not be used to derive any other statistics" (`_ReadMe_First_IndFin.txt`;
+likewise `UserGuide.xls` Data User Note 8: "Do not use the weight field to
+derive state or national totals"). The raw encoding is also inconsistent
+across vintages (reciprocal scale most years, direct scale in 2003, a `1`
+placeholder in 1967/70/71/73/2001, all-`0` in 2007–2012, `NA` for all
+modern-source rows), so `sum(amt * survey_weight/10000)`-style expressions
+produce silently wrong totals — including exact zeros for 2007–2012. Sum
+`amt` unweighted; no uscogdata function reads this column. Full evidence:
+`cog_pipeline/.superpowers/sdd/weight-semantics-findings.md`.
 
 ## Developer notes
 
 ### Testing
 
 The package ships a bundled fixture corpus at `inst/extdata/fixture_corpus/` —
-a 15 MB four-year slice (2011, 2012, 2019, 2020) of the full corpus covering
-all 50 states. `tests/testthat/setup.R` automatically points `USCOGDATA_URL`
-at this fixture, so the full test suite runs offline with no network
-dependency:
+a 3.6 MB two-year slice (2019 + 2020) of the full corpus covering all 50
+states. `tests/testthat/setup.R` automatically points `USCOGDATA_URL` at this
+fixture, so the full test suite runs offline with no network dependency:
 
 ```r
 devtools::test()   # uses bundled fixture, no credentials required

data-raw/measure_signposting_rate.R

@@ -0,0 +1,563 @@
+# data-raw/measure_signposting_rate.R
+#
+# Phase R3 Task 19c: measures the harmonization-signposting suggestion rate
+# under THREE `.build_suggestions()` implementations, over a realistic query
+# battery:
+#   every summary_categories category
+#     x a 3-year pre/post-2012 span (the wide-aggregate -> modern-leaf
+#       format-boundary window; falls back to the widest span the corpus
+#       actually supports if it can't fill a full 3+3 design -- see
+#       .measure_year_span())
+#     x up to N_GOV sampled governments (seeded, deterministic)
+#
+# The three arms, oldest to newest:
+#   - "coarse"  (git ref b0df1ec, the merged R2 tip): a year counts as
+#     gapped only when the WHOLE category result has zero rows that year.
+#   - "selfcov" (git ref da72bf3, Task 19c's first per-code pass, since
+#     amended after review): per-code, but a component's gap could be
+#     satisfied by ANY component of the recipe INCLUDING ITSELF -- so a
+#     code whose only representation in a year was its own wide-era
+#     aggregate row satisfied its own coverage check. Flagged in review as
+#     not matching review-doc S: 0.3's literal criterion ("... has no rows
+#     ... but OTHER components do") and fixed in the next commit.
+#   - "percode" (live code): per-code, requiring a genuinely DIFFERENT
+#     sibling component to supply the covering evidence -- the shipped,
+#     corrected implementation.
+#
+# READ THIS BEFORE QUOTING ANY DELTA FROM THIS SCRIPT
+# -----------------------------------------------------
+# The coarse and per-code checks are PARTLY DISJOINT, not nested. Per-code
+# is NOT a strict widening of coarse: there are queries coarse fires on that
+# per-code does not, so moving coarse -> percode both ADDS and REMOVES
+# signposting. Every `*_delta_pp` figure this script reports -- overall and
+# per category -- is therefore a NET of those two flows and can mask a
+# coverage loss in either direction. A headline "+X pp" can sit on top of
+# categories that lost coverage outright (a NEGATIVE corrected_delta_pp),
+# and a category-level zero can be an add and a loss cancelling. Read
+# `$subset_relation` (printed under "Subset relation" below) alongside any
+# delta; that section is where the two flows are separated.
+#
+# The disjointness is structural, not a sampling artifact. Both arms pair a
+# gap test with a coverage test, and it is the COVERAGE test that differs:
+#   - coarse:  gap = the WHOLE category result has zero rows that year;
+#              covered = the recipe's generic join has ANY row that year
+#              (unioned across all components -- a component's own
+#              aggregate row counts).
+#   - percode: gap = one specific component has no non-aggregate row that
+#              year; covered = a DIFFERENT component of the SAME recipe has
+#              a row that year (self-coverage explicitly excluded, per
+#              review-doc S: 0.3's "...but OTHER components do").
+# So when a whole category is empty in a year -- exactly coarse's trigger --
+# and the only covering evidence is the gapped component's own wide-era
+# aggregate row, coarse fires and per-code CANNOT: there is by construction
+# no other component to supply the evidence. That case is already pinned as
+# intended behaviour in tests/testthat/test-recipes.R ("per-code gap does
+# NOT fire when a code's only coverage is its own aggregate row"). This
+# script's job is to say how often it costs coverage, not to relitigate it.
+#
+# This script MEASURES the deltas; it does not decide whether the resulting
+# signposting trade -- added "noise" in one direction, lost whole-category
+# gap coverage in the other -- is acceptable. That is Jared's ruling at
+# Checkpoint R3 (see
+# cog_pipeline/.superpowers/sdd/phase-r-task-19c-brief.md). The selfcov arm
+# exists purely to answer a narrower, mechanical question for that ruling:
+# how much of the coarse -> percode delta was ever attributable to the
+# self-coverage bug (selfcov -> percode), as opposed to genuine
+# other-component coverage (coarse -> percode directly)?
+#
+# All three arms no longer coexist in R/suggestions.R (each superseded the
+# last in place), so this script pulls each VERBATIM from git history and
+# evaluates it in an isolated environment parented on the uscogdata
+# namespace, so each still resolves the unchanged sibling helpers it
+# depends on (.sql_lit_chr()) exactly as the live package did at that
+# commit. This guarantees every non-live arm is the actual shipped code at
+# that point, not a hand-reconstruction that could silently drift from what
+# really shipped.
+#
+# Usage (from the uscogdata package root; a git checkout, not a tarball):
+#   Rscript data-raw/measure_signposting_rate.R
+#   USCOGDATA_URL=<staged-corpus-url> Rscript data-raw/measure_signposting_rate.R
+#
+# Or from R:
+#   source("data-raw/measure_signposting_rate.R")
+#   res <- measure_signposting_rate(corpus_url = "<url>")
+#   res$summary; res$by_category
+
+#' Pull a historical `.build_suggestions()` (and whatever helpers it uses)
+#' verbatim from git history and evaluate it in an isolated environment
+#' parented on the uscogdata namespace, so it resolves unchanged sibling
+#' helpers (`.sql_lit_chr()`) the same way the live package does.
+#' @noRd
+.measure_load_git_impl <- function(git_ref, git_path = "R/suggestions.R") {
+  old_src <- tryCatch(
+    system2("git", c("show", sprintf("%s:%s", git_ref, git_path)),
+            stdout = TRUE, stderr = TRUE),
+    error = function(e) NULL
+  )
+  status <- attr(old_src, "status")
+  if (is.null(old_src) || (!is.null(status) && status != 0L) ||
+      !any(grepl("^\\.build_suggestions", old_src))) {
+    stop(
+      "Could not retrieve the .build_suggestions() implementation from ",
+      "git ref '", git_ref, "' at '", git_path, "'. Run this script from ",
+      "inside the uscogdata git checkout (not a tarball/installed copy).",
+      call. = FALSE
+    )
+  }
+  env <- new.env(parent = asNamespace("uscogdata"))
+  # eval(parse()) here is safe: `old_src` is not external/untrusted input --
+  # it is this repo's OWN historical R/suggestions.R, fetched via `git show`
+  # from a fixed, hardcoded internal commit ref (overridable only by a
+  # caller who already has R-level code execution in this dev-only
+  # measurement script). No network or user-supplied data reaches this call.
+  eval(parse(text = old_src), envir = env)
+  stopifnot(is.function(env$.build_suggestions))
+  env
+}
+
+#' Resolve the query battery's year span: a `pre_n`-year window immediately
+#' before `boundary_year` unioned with a `post_n`-year window starting at
+#' `boundary_year` (default 3+3 around 2012, the wide-aggregate ->
+#' modern-leaf format boundary). Falls back to every distinct year the
+#' corpus actually has in `long` when it can't fill that full design, and
+#' says so explicitly in `$note` rather than silently padding or
+#' fabricating years.
+#' @noRd
+.measure_year_span <- function(con, boundary_year = 2012L,
+                                pre_n = 3L, post_n = 3L) {
+  available <- sort(as.integer(
+    DBI::dbGetQuery(con, "SELECT DISTINCT year FROM long")$year
+  ))
+  desired_pre  <- (boundary_year - pre_n):(boundary_year - 1L)
+  desired_post <- boundary_year:(boundary_year + post_n - 1L)
+  actual_pre   <- intersect(desired_pre, available)
+  actual_post  <- intersect(desired_post, available)
+  full_design  <- length(actual_pre) == pre_n && length(actual_post) == post_n
+
+  if (full_design) {
+    years <- sort(c(actual_pre, actual_post))
+    note <- sprintf(
+      "Full %d-year pre/%d-year post-%d design available -- using years: %s.",
+      pre_n, post_n, boundary_year, paste(years, collapse = ", ")
+    )
+  } else {
+    years <- available
+    note <- sprintf(paste(
+      "Corpus does NOT support a full %d-year pre/%d-year post-%d span",
+      "(desired pre-window %s -> only %s present; desired post-window %s",
+      "-> only %s present). Falling back to the WIDEST span this corpus",
+      "supports: all %d distinct year(s) actually in `long`: %s.",
+      "This is NOT a 3-year pre/post-%d design -- reported as measured,",
+      "not padded or fabricated."
+    ),
+    pre_n, post_n, boundary_year,
+    paste(desired_pre, collapse = ","),
+    if (length(actual_pre)) paste(actual_pre, collapse = ",") else "none",
+    paste(desired_post, collapse = ","),
+    if (length(actual_post)) paste(actual_post, collapse = ",") else "none",
+    length(available), paste(available, collapse = ", "),
+    boundary_year)
+  }
+  list(years = years, full_design = full_design, note = note,
+       available = available)
+}
+
+#' Deterministically sample up to `n` distinct governments that actually
+#' report *something* in the battery's year span (querying a government
+#' with zero presence in every measured year isn't a realistic query).
+#' @noRd
+.measure_sample_govids <- function(con, years, n = 20L, seed = 19L) {
+  pool <- DBI::dbGetQuery(con, sprintf(
+    "SELECT DISTINCT canonical_govid FROM long WHERE year IN (%s)
+     ORDER BY canonical_govid",
+    paste(years, collapse = ",")
+  ))$canonical_govid
+  if (length(pool) <= n) return(sort(pool))
+  set.seed(seed)
+  sort(sample(pool, n))
+}
+
+#' Comma-join a suggestion list's recipe ids (stable order) for the detail
+#' frame's audit columns; `""` when nothing fired.
+#' @noRd
+.measure_recipe_ids <- function(suggestions) {
+  if (length(suggestions) == 0L) return("")
+  paste(sort(vapply(suggestions, function(s) s$recipe_id, character(1))),
+        collapse = ",")
+}
+
+#' Run one (category, government) query through the coarse (`coarse_env`),
+#' self-coverage-allowed (`selfcov_env`), and live per-code
+#' `.build_suggestions()` and return a one-row summary of what each fired.
+#'
+#' Also records the coarse arm's OWN trigger evidence -- `coarse_gap_years`,
+#' the requested years in which the whole category result has zero rows --
+#' so a coarse-fired/per-code-silent disagreement can be named down to
+#' (category, government, year) instead of just counted. Per-code's gap
+#' years are deliberately NOT re-derived here: that would mean
+#' reimplementing `.recipe_component_gapped()`'s set arithmetic in the
+#' measurement harness, where it could silently drift from the code under
+#' measurement. Per-code rows are identified by the recipe ids they fired.
+#' @noRd
+.measure_one_query <- function(con, coarse_env, selfcov_env, category,
+                                category_type, govid, years) {
+  view        <- if (identical(category_type, "revenue")) {
+    "revenue_annotated_harmonized"
+  } else {
+    "spending_annotated_harmonized"
+  }
+  subtype_col <- if (identical(category_type, "revenue")) {
+    "revenue_subtype"
+  } else {
+    "spend_subtype"
+  }
+  sql    <- .build_verb_sql(view, subtype_col, govid, years, category)
+  result <- tibble::as_tibble(DBI::dbGetQuery(con, sql))
+
+  coarse_sugg  <- coarse_env$.build_suggestions(
+    con, govid, years, category, result, "harmonized"
+  )
+  selfcov_sugg <- selfcov_env$.build_suggestions(
+    con, govid, years, category, "harmonized"
+  )
+  percode_sugg <- .build_suggestions(con, govid, years, category, "harmonized")
+
+  result_years <- if (nrow(result) == 0L) integer(0) else unique(as.integer(result$year))
+  gap_years    <- sort(setdiff(as.integer(years), result_years))
+
+  data.frame(
+    category         = category,
+    category_type    = category_type,
+    canonical_govid  = govid,
+    n_result_rows    = nrow(result),
+    coarse_gap_years = paste(gap_years, collapse = ","),
+    n_coarse         = length(coarse_sugg),
+    n_selfcov        = length(selfcov_sugg),
+    n_percode        = length(percode_sugg),
+    fired_coarse     = length(coarse_sugg) > 0L,
+    fired_selfcov    = length(selfcov_sugg) > 0L,
+    fired_percode    = length(percode_sugg) > 0L,
+    coarse_recipes   = .measure_recipe_ids(coarse_sugg),
+    percode_recipes  = .measure_recipe_ids(percode_sugg),
+    stringsAsFactors = FALSE
+  )
+}
+
+#' Columns that identify a disagreeing query well enough for a human to go
+#' and inspect it, in print order. Intersected with what `detail` actually
+#' has, so this works on a minimal hand-built frame too.
+#' @noRd
+.MEASURE_IDENTITY_COLS <- c(
+  "category", "category_type", "canonical_govid", "coarse_gap_years",
+  "n_result_rows", "coarse_recipes", "percode_recipes"
+)
+
+#' Separate the two flows the `*_delta_pp` figures net together.
+#'
+#' Per-code is NOT a widening of coarse (see this file's header): the two
+#' checks pair different gap tests with different coverage tests, so moving
+#' coarse -> percode both adds and removes firings. This splits the
+#' disagreement into:
+#'   - `violations`: coarse fired, per-code did NOT -- signposting coverage
+#'     LOST. These are what a net delta hides. `holds` is FALSE whenever
+#'     this is non-empty, i.e. whenever coarse is not a subset of per-code.
+#'   - `additions`: per-code fired, coarse did NOT -- the expected gain.
+#'
+#' Deliberately returns the offending rows, not just counts, so the
+#' Checkpoint R3 ruling can be made against named (category, government,
+#' year) cases. Deliberately does NOT assert -- the violation set is really
+#' non-empty on the staged corpus, and a hard assertion here would only
+#' break the harness that is supposed to report it.
+#' @noRd
+.measure_subset_relation <- function(detail) {
+  required <- c("category", "canonical_govid", "fired_coarse", "fired_percode")
+  absent   <- if (is.data.frame(detail)) setdiff(required, names(detail)) else required
+  if (!is.data.frame(detail) || length(absent) > 0L) {
+    stop("`detail` must be a data frame with columns ",
+         paste(required, collapse = ", "), " (missing: ",
+         paste(absent, collapse = ", "), ").", call. = FALSE)
+  }
+  fired_coarse  <- as.logical(detail$fired_coarse)
+  fired_percode <- as.logical(detail$fired_percode)
+  if (anyNA(fired_coarse) || anyNA(fired_percode)) {
+    stop("`fired_coarse`/`fired_percode` must be non-NA logicals.", call. = FALSE)
+  }
+
+  keep     <- intersect(.MEASURE_IDENTITY_COLS, names(detail))
+  viol_idx <- which(fired_coarse & !fired_percode)
+  add_idx  <- which(fired_percode & !fired_coarse)
+
+  list(
+    holds          = length(viol_idx) == 0L,
+    n_queries      = nrow(detail),
+    n_coarse_fired = sum(fired_coarse),
+    n_percode_fired = sum(fired_percode),
+    n_both         = sum(fired_coarse & fired_percode),
+    n_violations   = length(viol_idx),
+    n_additions    = length(add_idx),
+    violations     = detail[viol_idx, keep, drop = FALSE],
+    additions      = detail[add_idx, keep, drop = FALSE]
+  )
+}
+
+#' Render a data frame of disagreeing queries as indented report lines,
+#' capped at `max_rows` with an explicit note about what was withheld (the
+#' full set is always in the returned `$subset_relation`).
+#' @noRd
+.measure_fmt_rows <- function(df, max_rows = 50L) {
+  if (nrow(df) == 0L) return("    (none)")
+  shown <- utils::head(df, max_rows)
+  out   <- paste0("    ", utils::capture.output(print(shown, row.names = FALSE)))
+  if (nrow(df) > max_rows) {
+    out <- c(out, sprintf("    ... %d more row(s) not shown; full set in $subset_relation.",
+                          nrow(df) - max_rows))
+  }
+  out
+}
+
+#' Format `.measure_subset_relation()` as a prominent, clearly-labelled
+#' report section. States plainly whether coarse is a subset of per-code
+#' and, when it is not, exactly where it breaks.
+#' @noRd
+.measure_format_subset_report <- function(rel, max_rows = 50L) {
+  lines <- c(
+    "==== Subset relation: is COARSE a subset of PER-CODE? ====",
+    sprintf("Queries: %d  |  coarse fired: %d  |  per-code fired: %d  |  both: %d",
+            rel$n_queries, rel$n_coarse_fired, rel$n_percode_fired, rel$n_both)
+  )
+  if (rel$holds) {
+    lines <- c(lines, sprintf(paste(
+      "HOLDS: coarse IS a subset of per-code -- 0 of %d queries fire under",
+      "coarse but not per-code. On THIS battery the delta is a pure",
+      "addition of %d query/queries, with no coverage lost."
+    ), rel$n_queries, rel$n_additions))
+  } else {
+    lines <- c(lines,
+      "*** VIOLATED: coarse is NOT a subset of per-code. ***",
+      sprintf(paste(
+        "%d of %d queries fire under COARSE but NOT under PER-CODE:",
+        "signposting coverage the move LOSES."
+      ), rel$n_violations, rel$n_queries),
+      sprintf(paste(
+        "Every delta reported above is therefore a NET of %d addition(s)",
+        "MINUS %d loss(es), and understates both. Do not read it as",
+        "'per-code fires wherever coarse did, plus more'."
+      ), rel$n_additions, rel$n_violations),
+      "",
+      paste("  COVERAGE LOST -- coarse fired, per-code silent.",
+            "`coarse_gap_years` is the requested year(s) in which the whole",
+            "category result was empty (coarse's own trigger evidence):"),
+      .measure_fmt_rows(rel$violations, max_rows)
+    )
+  }
+  c(lines, "",
+    sprintf("  COVERAGE ADDED -- per-code fired, coarse silent (%d query/queries):",
+            rel$n_additions),
+    .measure_fmt_rows(rel$additions, max_rows))
+}
+
+#' Measure the coarse-vs-per-code signposting suggestion rate over a
+#' realistic query battery (every category x a pre/post-boundary_year span
+#' x up to n_gov sampled governments).
+#'
+#' @param corpus_url Corpus to measure against. Defaults to
+#'   `Sys.getenv("USCOGDATA_URL")`; if that's unset, falls back to the
+#'   bundled v5 fixture (so the script runs out of the box). Re-run with
+#'   `USCOGDATA_URL` pointed at the staged/full corpus later.
+#' @param n_gov Governments to sample (deterministically). "Up to" -- if
+#'   the corpus has fewer distinct governments in the measured years than
+#'   this, every one of them is used.
+#' @param seed Sampling seed (fixed for reproducibility).
+#' @param boundary_year,pre_years_n,post_years_n Define the desired query
+#'   span: `pre_years_n` years immediately before `boundary_year`, unioned
+#'   with `post_years_n` years starting at `boundary_year`. Falls back to
+#'   the corpus's widest actually-available span when this can't be filled
+#'   (see `.measure_year_span()`).
+#' @param coarse_ref Git ref to pull the R2 coarse `.build_suggestions()`
+#'   from.
+#' @param selfcov_ref Git ref to pull Task 19c's first, self-coverage-
+#'   allowed per-code `.build_suggestions()` from (amended after review).
+#' @param verbose Print progress/notes as the battery runs.
+#' @return Invisibly, a list with `corpus_url`, `years`, `span_note`,
+#'   `full_design`, `govids`, `seed`, `detail` (one row per query),
+#'   `by_category`, and `summary`.
+#' @noRd
+measure_signposting_rate <- function(corpus_url = Sys.getenv("USCOGDATA_URL", unset = NA),
+                                      n_gov = 20L,
+                                      seed = 19L,
+                                      boundary_year = 2012L,
+                                      pre_years_n = 3L,
+                                      post_years_n = 3L,
+                                      coarse_ref = "b0df1ec",
+                                      selfcov_ref = "da72bf3",
+                                      verbose = TRUE) {
+  pkgload::load_all(".", quiet = TRUE)
+
+  if (is.na(corpus_url) || !nzchar(corpus_url)) {
+    corpus_url <- paste0(
+      system.file("extdata/fixture_corpus", package = "uscogdata"), "/"
+    )
+    if (verbose) {
+      message("No USCOGDATA_URL set; defaulting to the bundled v5 fixture: ",
+              corpus_url)
+    }
+  }
+
+  old_url <- Sys.getenv("USCOGDATA_URL", unset = NA)
+  cog_close()
+  Sys.setenv(USCOGDATA_URL = corpus_url)
+  on.exit({
+    cog_close()
+    if (is.na(old_url)) Sys.unsetenv("USCOGDATA_URL") else Sys.setenv(USCOGDATA_URL = old_url)
+  }, add = TRUE)
+
+  con <- cog_open()
+  coarse_env  <- .measure_load_git_impl(git_ref = coarse_ref)
+  selfcov_env <- .measure_load_git_impl(git_ref = selfcov_ref)
+
+  span   <- .measure_year_span(con, boundary_year, pre_years_n, post_years_n)
+  years  <- span$years
+  if (verbose) message(span$note)
+
+  govids <- .measure_sample_govids(con, years, n = n_gov, seed = seed)
+  if (verbose) {
+    message(sprintf("Sampled %d government(s) (seed = %d) from %d present in years %s.",
+                     length(govids), seed,
+                     length(DBI::dbGetQuery(con, sprintf(
+                       "SELECT DISTINCT canonical_govid FROM long WHERE year IN (%s)",
+                       paste(years, collapse = ",")))$canonical_govid),
+                     paste(years, collapse = ", ")))
+  }
+
+  categories <- DBI::dbGetQuery(con,
+    "SELECT DISTINCT category, category_type FROM summary_categories
+     WHERE category IS NOT NULL ORDER BY category_type, category")
+  if (verbose) {
+    message(sprintf("Battery: %d categories x %d governments = %d queries.",
+                     nrow(categories), length(govids),
+                     nrow(categories) * length(govids)))
+  }
+
+  rows <- vector("list", nrow(categories) * length(govids))
+  k <- 0L
+  for (ci in seq_len(nrow(categories))) {
+    for (gv in govids) {
+      k <- k + 1L
+      rows[[k]] <- .measure_one_query(
+        con, coarse_env, selfcov_env,
+        category = categories$category[ci],
+        category_type = categories$category_type[ci],
+        govid = gv, years = years
+      )
+    }
+  }
+  detail <- do.call(rbind, rows)
+  # percode only ever fires where selfcov also fires (percode is a strict
+  # narrowing of selfcov: same gap detection, plus the self-coverage path
+  # removed) -- this is what makes the decomposition below exact rather
+  # than approximate. Checked, not assumed.
+  stopifnot(all(detail$fired_percode <= detail$fired_selfcov))
+  detail$fired_selfcov_only <- detail$fired_selfcov & !detail$fired_percode
+
+  # coarse vs percode is NOT a subset relation the way percode vs selfcov
+  # is (see header). Measured and REPORTED, never asserted: the violation
+  # set is genuinely non-empty on the staged corpus, and a stopifnot() here
+  # would break the harness whose whole job is to surface it.
+  subset_relation <- .measure_subset_relation(detail)
+  detail$coarse_only  <- detail$fired_coarse & !detail$fired_percode
+  detail$percode_only <- detail$fired_percode & !detail$fired_coarse
+
+  by_category <- dplyr::summarise(
+    dplyr::group_by(detail, category, category_type),
+    n_queries      = dplyr::n(),
+    coarse_rate    = mean(fired_coarse),
+    selfcov_rate   = mean(fired_selfcov),
+    percode_rate   = mean(fired_percode),
+    original_delta_pp  = (mean(fired_selfcov) - mean(fired_coarse)) * 100,
+    corrected_delta_pp = (mean(fired_percode) - mean(fired_coarse)) * 100,
+    selfcov_share_pp    = mean(fired_selfcov_only) * 100,
+    # the two flows corrected_delta_pp nets together, per category
+    n_coarse_only  = sum(coarse_only),
+    n_percode_only = sum(percode_only),
+    .groups = "drop"
+  )
+  by_category <- dplyr::arrange(by_category, dplyr::desc(corrected_delta_pp))
+
+  summary_overall <- data.frame(
+    n_queries     = nrow(detail),
+    n_categories  = nrow(categories),
+    n_governments = length(govids),
+    coarse_fired  = sum(detail$fired_coarse),
+    selfcov_fired = sum(detail$fired_selfcov),
+    percode_fired = sum(detail$fired_percode),
+    coarse_rate   = mean(detail$fired_coarse),
+    selfcov_rate  = mean(detail$fired_selfcov),
+    percode_rate  = mean(detail$fired_percode)
+  )
+  summary_overall$original_delta_pp  <- (summary_overall$selfcov_rate - summary_overall$coarse_rate) * 100
+  summary_overall$corrected_delta_pp <- (summary_overall$percode_rate - summary_overall$coarse_rate) * 100
+  summary_overall$selfcov_share_pp   <- mean(detail$fired_selfcov_only) * 100
+  summary_overall$relative_increase  <- if (summary_overall$coarse_rate > 0) {
+    summary_overall$percode_rate / summary_overall$coarse_rate - 1
+  } else {
+    NA_real_
+  }
+
+  if (verbose) {
+    message(sprintf(
+      "Coarse rate: %.4f (%d/%d)  |  Self-cov-allowed rate: %.4f (%d/%d)  |  Corrected per-code rate: %.4f (%d/%d)",
+      summary_overall$coarse_rate, summary_overall$coarse_fired, summary_overall$n_queries,
+      summary_overall$selfcov_rate, summary_overall$selfcov_fired, summary_overall$n_queries,
+      summary_overall$percode_rate, summary_overall$percode_fired, summary_overall$n_queries
+    ))
+    message(sprintf(
+      "Original delta (selfcov - coarse): %+.2f pp  |  Corrected delta (percode - coarse): %+.2f pp  |  Self-coverage share of original delta: %.2f pp (%d/%d queries fired ONLY via self-coverage)",
+      summary_overall$original_delta_pp, summary_overall$corrected_delta_pp,
+      summary_overall$selfcov_share_pp,
+      sum(detail$fired_selfcov_only), summary_overall$n_queries
+    ))
+    message(if (subset_relation$holds) {
+      sprintf("Subset relation coarse <= percode HOLDS (0 coarse-only firings); delta is a pure addition of %d.",
+              subset_relation$n_additions)
+    } else {
+      sprintf("*** Subset relation coarse <= percode VIOLATED: %d coarse-only firing(s) LOST vs %d percode-only added. Deltas above are NETS. ***",
+              subset_relation$n_violations, subset_relation$n_additions)
+    })
+  }
+
+  invisible(list(
+    corpus_url      = corpus_url,
+    years           = years,
+    span_note       = span$note,
+    full_design     = span$full_design,
+    govids          = govids,
+    seed            = seed,
+    n_categories    = nrow(categories),
+    detail          = detail,
+    by_category     = by_category,
+    summary         = summary_overall,
+    subset_relation = subset_relation
+  ))
+}
+
+if (identical(environment(), globalenv()) && sys.nframe() == 0L) {
+  res <- measure_signposting_rate()
+  cat("\n==== Query battery ====\n")
+  cat("Corpus:", res$corpus_url, "\n")
+  cat("Years:", paste(res$years, collapse = ", "), "\n")
+  cat("Full 3-year pre/post-2012 design achieved:", res$full_design, "\n")
+  cat(res$span_note, "\n")
+  cat("Governments sampled:", length(res$govids), "\n\n")
+
+  cat("==== Overall summary (coarse / self-coverage-allowed / corrected per-code) ====\n")
+  print(res$summary)
+
+  cat("\n==== By category (sorted by corrected delta, descending) ====\n")
+  cat("NOTE: corrected_delta_pp is a NET. n_coarse_only = firings LOST going\n")
+  cat("coarse -> percode; n_percode_only = firings ADDED. A category can be\n")
+  cat("negative (net coverage loss) even when the overall figure is positive.\n")
+  print(as.data.frame(res$by_category), row.names = FALSE)
+
+  cat("\n")
+  cat(paste(.measure_format_subset_report(res$subset_relation), collapse = "\n"), "\n")
+}

inst/extdata/fixture_corpus/manifest.json

@@ -1,7 +1,7 @@
 {
   "schema_version": 6,
-  "built_at": "2026-07-27T13:04:05Z",
-  "pipeline_commit": "6098baf",
+  "built_at": "2026-07-23T16:14:30Z",
+  "pipeline_commit": "4f992a0",
   "fixture_note": "Four-year (2011, 2012, 2019, 2020) fixture for uscogdata tests. Full corpus available via USCOGDATA_URL. Regenerated for Phase R2 (schema_version 5, harmonization_map/harmonization_recipes/ series_breaks parquet tables added). 2011/2012 straddle the wide-aggregate -> modern-leaf format boundary exercised by basis= \"harmonized\" and recipe= queries; 2019/2020 retain the prior per-capita/CPI regression anchors. Full canonical_fips_xwalk master and canonical_alias lookup table included via data-raw/regenerate_fixture_corpus.R.",
   "data_vintage": {
     "source_vintages": {
@@ -75,7 +75,7 @@
       },
       {
         "path": "data/summary_categories.parquet",
-        "sha256": "0985b607f3f35a8dff62c0561261ab6922423b81d11c07b03bcb3e3461f85e33",
+        "sha256": "8e6fcd4dd9bb4723841a67233b19388c9762dfc23b4479501183cebf7ea3c1b5",
         "description": "summary_categories.parquet"
       },
       {

inst/schemas/provenance-v1.json

@@ -12,19 +12,6 @@
     "category":       { "type": ["string", "array", "null"] },
     "basis":          { "type": ["string", "null"] },
     "basis_note":     { "type": ["string", "null"] },
-    "expenditure_concept": {
-      "type": "string",
-      "enum": ["direct", "total"],
-      "description": "Which spending concept produced this result. 'direct' is the government's own E/F/G spending; 'total' adds its intergovernmental payments (M to local governments, L to state governments). Only 'direct' is valid for results combined across governments."
-    },
-    "expenditure_concept_note": {
-      "type": ["string", "null"],
-      "description": "How the intergovernmental leg was assembled; null for 'direct'."
-    },
-    "expenditure_concept_direct_suppressed": {
-      "type": "boolean",
-      "description": "TRUE when expenditure_concept = 'total' and at least one requested (year, category) has intergovernmental rows but NO Direct rows in this corpus (typically a legacy aggregate-only family) -- those result rows report the intergovernmental leg alone, not Direct + IG. Always FALSE for expenditure_concept = 'direct'. See the affected rows' `notes` for the recovering recipe, if any."
-    },
     "harmonization":  { "type": "object" },
     "recipe":         { "type": ["object", "null"] },
     "suggestions":    { "type": "array" },

inst/sql/20-spending_long.sql

@@ -1,5 +1,5 @@
 CREATE OR REPLACE VIEW spending_long AS
 SELECT *
 FROM long
-WHERE LEFT(item_code, 1) IN ('E', 'F', 'G')
+WHERE LEFT(item_code, 1) IN ('E', 'F', 'G', 'K')
   AND NOT is_aggregate;

inst/sql/22-spending_long_harmonized.sql

@@ -3,4 +3,4 @@ SELECT * REPLACE (harmonized_code AS item_code)
 FROM long
 WHERE NOT is_aggregate
   AND harmonized_code IS NOT NULL
-  AND LEFT(harmonized_code, 1) IN ('E', 'F', 'G');
+  AND LEFT(harmonized_code, 1) IN ('E', 'F', 'G', 'K');

inst/sql/24-ig_long.sql

@@ -1,18 +0,0 @@
--- Intergovernmental expenditure rows (M = to local govts, L = to state govts).
---
--- Deliberately does NOT filter `NOT is_aggregate`, unlike spending_long. In the
--- wide era (<= FY2011) the IG families M05/M12/M47/M89/L47/L89 are published
--- ONLY as aggregate-flagged rows -- filtering them would hide ~70% of legacy IG
--- dollars and make Total silently collapse to Direct. This is safe because the
--- aggregate codes and their modern leaf components are strictly year-disjoint
--- (M47 ends 2011 / M94 starts 2012; M89 is aggregate only <= 2011 and a leaf
--- from 2012 alongside M91-93), so no row is ever counted twice. Same argument
--- the pipeline's recipe joins use.
---
--- `L--` IS excluded: it is the IG-to-state FAMILY TOTAL and genuinely rolls up
--- the L-NN codes, so including it would double-count.
-CREATE OR REPLACE VIEW ig_long AS
-SELECT *
-FROM long
-WHERE LEFT(item_code, 1) IN ('M', 'L')
-  AND item_code NOT LIKE '%--';

inst/sql/25-ig_long_harmonized.sql

@@ -1,15 +0,0 @@
--- Harmonized-basis IG rows. Uses COALESCE(harmonized_code, item_code) rather
--- than harmonized_code alone: aggregate rows carry NO harmonized_code by
--- construction (harmonized space is leaf-only), so a plain
--- `harmonized_code IS NOT NULL` filter would drop every legacy IG aggregate --
--- in the bundled fixture corpus (year 2011; 2012+ all carry a harmonized_code)
--- that is $379,016,063k across 25,688 M rows and $2,277,458k across 19,266 L
--- rows (`SELECT year, LEFT(item_code,1), SUM(amt), COUNT(*) FROM ig_long
--- WHERE harmonized_code IS NULL GROUP BY 1, 2`). COALESCE keeps the one real
--- IG collapse rule (M38 -> M36, SB012, year-disjoint 1967-2011 vs 2012+)
--- while never dropping a row.
-CREATE OR REPLACE VIEW ig_long_harmonized AS
-SELECT * REPLACE (COALESCE(harmonized_code, item_code) AS item_code)
-FROM long
-WHERE LEFT(item_code, 1) IN ('M', 'L')
-  AND item_code NOT LIKE '%--';

inst/sql/44-ig_annotated.sql

@@ -1,16 +0,0 @@
-CREATE OR REPLACE VIEW ig_annotated AS
-SELECT
-  s.*,
-  x.gov_name       AS xwalk_gov_name,
-  x.govs_type,
-  x.type_label,
-  x.fips_state     AS xwalk_fips_state,
-  x.fips_county    AS xwalk_fips_county,
-  x.fips_place,
-  x.population_acs,
-  c.category,
-  c.category_type,
-  c.spend_subtype
-FROM ig_long s
-LEFT JOIN canonical_fips_xwalk x USING (canonical_govid)
-LEFT JOIN summary_categories   c USING (item_code);

inst/sql/45-ig_annotated_harmonized.sql

@@ -1,16 +0,0 @@
-CREATE OR REPLACE VIEW ig_annotated_harmonized AS
-SELECT
-  s.*,
-  x.gov_name       AS xwalk_gov_name,
-  x.govs_type,
-  x.type_label,
-  x.fips_state     AS xwalk_fips_state,
-  x.fips_county    AS xwalk_fips_county,
-  x.fips_place,
-  x.population_acs,
-  c.category,
-  c.category_type,
-  c.spend_subtype
-FROM ig_long_harmonized s
-LEFT JOIN canonical_fips_xwalk x USING (canonical_govid)
-LEFT JOIN summary_categories   c USING (item_code);

man/cog_geographic_rollup.Rd

@@ -9,8 +9,7 @@ cog_geographic_rollup(
   category,
   years,
   per_capita = FALSE,
-  adjust_to_year = NULL,
-  expenditure_concept = c("direct", "total")
+  adjust_to_year = NULL
 )
 }
 \arguments{
@@ -28,13 +27,6 @@ population from `gov_population_yearly`. Govs with missing population
 are excluded from the result.}
 
 \item{adjust_to_year}{Integer base year for CPI-U conversion, or `NULL`.}
-
-\item{expenditure_concept}{`"direct"` (default) or `"total"`. Currently only
-`"direct"` is accepted; the `"total"` option exists in [cog_spending()] for
-single-government queries but cannot be used here because combining Total
-across multiple layers of government double-counts intergovernmental
-transfers (a state's payment to a school district is the same dollar the
-district reports as its own Direct spending).}
 }
 \value{
 Tibble with columns `year`, `layer`, `canonical_govid`, `gov_name`,

man/cog_peer_compare.Rd

@@ -10,8 +10,7 @@ cog_peer_compare(
   category,
   years,
   per_capita = TRUE,
-  adjust_to_year = NULL,
-  expenditure_concept = c("direct", "total")
+  adjust_to_year = NULL
 )
 }
 \arguments{
@@ -28,11 +27,6 @@ cog_peer_compare(
 population.}
 
 \item{adjust_to_year}{Integer base year for CPI-U conversion or `NULL`.}
-
-\item{expenditure_concept}{`"direct"` (default) or `"total"`. Currently only
-`"direct"` is accepted; the `"total"` option exists in [cog_spending()] for
-single-government queries but cannot be used here because combining Total
-across peer sets counts intergovernmental transfers twice.}
 }
 \value{
 Tibble matching [cog_spending()]'s columns, plus a `role`

man/cog_spending.Rd

@@ -11,8 +11,7 @@ cog_spending(
   per_capita = FALSE,
   adjust_to_year = NULL,
   basis = c("harmonized", "raw"),
-  recipe = NULL,
-  expenditure_concept = c("direct", "total")
+  recipe = NULL
 )
 }
 \arguments{
@@ -56,35 +55,6 @@ argument is ignored and the result's provenance reports
 `basis = "recipe"` with an inert `harmonization` block (`applied =
 FALSE`, pointing at the `recipe` block instead) rather than a
 possibly-misleading `"harmonized"`/`"raw"` value.}
-
-\item{expenditure_concept}{`"direct"` (default) returns only the
-government's own direct spending (item codes `E`/`F`/`G`), unchanged
-from prior releases. `"total"` additionally UNIONs in the
-intergovernmental leg -- payments to local governments (`M` codes) and
-to the state government (`L` codes, excluding the `L--` family-total
-rollup) -- so results gain rows with `spend_subtype ==
-"intergovernmental"`. Requires the active corpus's `summary_categories`
-to carry M/L rows (added by cog_pipeline PR #59); aborts with class
-`uscogdata_ig_categories_unsupported` on an older corpus rather than
-silently under-reporting. Mutually exclusive with `recipe` (a recipe
-already defines its own component codes). **Do not sum `"total"`
-results across levels of government** (e.g. state + county + city):
-a state's `M12` payment to a school district is the same dollar the
-district reports as its own direct `E12`, so summing both double-counts
-it. This matters in particular with [cog_geographic_rollup()], which
-sums across exactly that kind of multi-layer government set.
-
-In the legacy wide era (<= FY2011), some functions are published ONLY
-as an aggregate-flagged family total (e.g. Corrections' `E04`/`E05`
-split), which the Direct leg excludes by construction but the IG leg
-deliberately keeps (see `inst/sql/24-ig_long.sql`). For a `"total"`
-query, any (year, category) where this leaves intergovernmental rows
-with NO Direct counterpart is flagged: the affected rows' `notes`
-name the harmonization recipe that recovers the missing Direct
-component (when one exists), and
-`provenance$expenditure_concept_direct_suppressed` is `TRUE` -- the
-figure in those rows is the intergovernmental leg alone, not Direct +
-IG.}
 }
 \value{
 Tibble with columns `year`, `canonical_govid`, `gov_name`,

tests/testthat/helper-fixture.R

@@ -57,37 +57,3 @@ with_doctored_schema_version <- function(version, code) {
   }, add = TRUE)
   force(code)
 }
-
-# Copy the bundled fixture to a temp dir with summary_categories.parquet
-# rewritten to drop every M/L (intergovernmental) row, then run `code`
-# against it with a clean session (mirrors with_fixture_corpus()/
-# with_doctored_schema_version()). Models a real pre-cog_pipeline-PR#59
-# corpus: the 66 M/L category rows shipped with NO schema_version bump (see
-# C2 in the expenditure-concept review), so schema_version is left
-# untouched here -- only the category data itself is rolled back.
-with_corpus_missing_ig_categories <- function(code) {
-  src <- fixture_corpus_path()
-  tmp <- withr::local_tempdir(.local_envir = parent.frame())
-  file.copy(list.files(src, full.names = TRUE), tmp, recursive = TRUE)
-
-  cats_path <- file.path(tmp, "data", "summary_categories.parquet")
-  filtered_path <- file.path(tmp, "data", "summary_categories_filtered.parquet")
-  write_con <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(write_con, shutdown = TRUE), add = TRUE)
-  DBI::dbExecute(write_con, sprintf(
-    "COPY (SELECT * FROM read_parquet(%s) WHERE LEFT(item_code, 1) NOT IN ('M', 'L'))
-     TO %s (FORMAT PARQUET)",
-    uscogdata:::.sql_lit_chr(cats_path), uscogdata:::.sql_lit_chr(filtered_path)
-  ))
-  file.remove(cats_path)
-  file.rename(filtered_path, cats_path)
-
-  old_url <- Sys.getenv("USCOGDATA_URL", unset = NA)
-  uscogdata:::cog_close()
-  Sys.setenv(USCOGDATA_URL = paste0(tmp, "/"))
-  on.exit({
-    uscogdata:::cog_close()
-    if (is.na(old_url)) Sys.unsetenv("USCOGDATA_URL") else Sys.setenv(USCOGDATA_URL = old_url)
-  }, add = TRUE)
-  force(code)
-}

tests/testthat/test-categories.R

@@ -15,18 +15,7 @@ test_that("cog_categories(type = 'spending') returns only expenditure rows", {
   skip_if_no_corpus()
   r <- cog_categories(type = "spending")
   expect_true(all(r$category_type == "expenditure"))
-  expect_true(all(r$subtype %in% c("operations", "capital", "intergovernmental")))
-})
-
-test_that("cog_categories surfaces the intergovernmental spending subtype", {
-  skip_if_no_corpus()
-  r <- cog_categories(type = "spending")
-  expect_true("intergovernmental" %in% r$subtype)
-  # IG rows reuse the existing functional categories -- they add a subtype,
-  # not new category values.
-  ig_cats     <- sort(unique(r$category[r$subtype == "intergovernmental"]))
-  direct_cats <- sort(unique(r$category[r$subtype != "intergovernmental"]))
-  expect_true(all(ig_cats %in% c(direct_cats, "Other Education")))
+  expect_true(all(r$subtype %in% c("operations", "capital")))
 })
 
 test_that("cog_categories(type = 'revenue') returns only revenue rows", {

tests/testthat/test-config.R

@@ -26,41 +26,3 @@ test_that(".resolve_cache_dir falls back to R_user_dir", {
     })
   })
 })
-
-# ---------------------------------------------------------------------------
-# Trailing-slash normalization (uscogdata #3 follow-up).
-#
-# EVERY consumer builds paths by concatenation: paste0(url, "manifest.json")
-# (manifest.R), paste0(url, e$path) (mirror.R), and the parquet glob in
-# views.R. mirror.R:104 even comments 'url ends in "/"' -- an assumption the
-# package documents and relies on but never enforced.
-#
-# A URL missing its trailing slash therefore fails SILENTLY and confusingly:
-#   HTTPS -> ".../downloadmanifest.json" -> the host answers with an HTML 404
-#            page -> the jsonlite lexical error that issue #3 reported;
-#   local -> ".../corpusdata/long/**/*.parquet" -> DuckDB "No files found".
-# Neither message points at the real cause. Normalize once, at resolution.
-# ---------------------------------------------------------------------------
-
-test_that(".resolve_url appends a missing trailing slash", {
-  withr::local_envvar(USCOGDATA_URL = "https://example.org/s/TOKEN/download")
-  expect_equal(.resolve_url(), "https://example.org/s/TOKEN/download/")
-})
-
-test_that(".resolve_url leaves an existing trailing slash alone", {
-  withr::local_envvar(USCOGDATA_URL = "https://example.org/s/TOKEN/download/")
-  expect_equal(.resolve_url(), "https://example.org/s/TOKEN/download/")
-})
-
-test_that(".resolve_url normalizes a local path without a trailing slash", {
-  withr::local_envvar(USCOGDATA_URL = "/tmp/corpus")
-  expect_equal(.resolve_url(), "/tmp/corpus/")
-})
-
-test_that(".resolve_url does not invent a slash for an empty setting", {
-  # An unset/empty URL must stay empty so the "not configured" guard in
-  # manifest.R still fires, rather than degrading into a bare "/" root.
-  withr::local_envvar(USCOGDATA_URL = "")
-  withr::local_options(uscogdata.url = "")
-  expect_equal(.resolve_url(), "")
-})

tests/testthat/test-expenditure-concept.R

@@ -1,536 +0,0 @@
-test_that("the corpus contains no K-prefix rows, so the Direct leg omits K", {
-  con <- .ensure_session()
-  n <- DBI::dbGetQuery(con,
-    "SELECT COUNT(*) AS n FROM long WHERE LEFT(item_code, 1) = 'K'")$n
-  expect_equal(n, 0)
-
-  sql_files <- c("20-spending_long.sql", "22-spending_long_harmonized.sql")
-  for (f in sql_files) {
-    txt <- paste(readLines(system.file("sql", f, package = "uscogdata")),
-                 collapse = " ")
-    expect_false(grepl("'K'", txt, fixed = TRUE),
-                 label = paste(f, "must not reference the inert K prefix"))
-  }
-})
-
-test_that("expenditure_concept defaults to direct and preserves today's numbers", {
-  gov <- "010000226085"                      # Alabama state government
-  base <- cog_spending(gov, years = 2019, category = "Police")
-  expl <- cog_spending(gov, years = 2019, category = "Police",
-                       expenditure_concept = "direct")
-  expect_equal(base$amt_nominal, expl$amt_nominal)
-  expect_false("intergovernmental" %in% base$spend_subtype)
-})
-
-test_that("expenditure_concept = 'total' adds an intergovernmental subtype", {
-  gov <- "010000226085"
-  d <- cog_spending(gov, years = 2019, category = "Police",
-                    expenditure_concept = "direct")
-  t <- cog_spending(gov, years = 2019, category = "Police",
-                    expenditure_concept = "total")
-  expect_true("intergovernmental" %in% t$spend_subtype)
-  # Direct rows are untouched; Total only ever ADDS. Use %in% rather than
-  # != : a category = NULL result can contain a NULL-subtype group (codes
-  # with no summary_categories row, e.g. E16/E21/E85/F16/F85/G16/G21/G85),
-  # and `NA != "intergovernmental"` is NA, not TRUE, which would silently
-  # smuggle an all-NA phantom row into dt.
-  dt <- t[!(t$spend_subtype %in% "intergovernmental"), ]
-  expect_equal(sort(dt$amt_nominal), sort(d$amt_nominal))
-  expect_gt(sum(t$amt_nominal), sum(d$amt_nominal))
-})
-
-test_that("legacy-era Total does not collapse to Direct (the is_aggregate trap)", {
-  # In the wide era the IG dollars live almost entirely on aggregate-flagged
-  # rows. A Total leg that inherited the Direct leg's NOT is_aggregate filter
-  # would silently return Total == Direct here.
-  gov <- "010000226085"
-  d <- cog_spending(gov, years = 2011, category = "Education K-12",
-                    expenditure_concept = "direct")
-  t <- cog_spending(gov, years = 2011, category = "Education K-12",
-                    expenditure_concept = "total")
-  expect_true("intergovernmental" %in% t$spend_subtype)
-  ig <- sum(t$amt_nominal[t$spend_subtype == "intergovernmental"])
-  expect_gt(ig, 0)
-  expect_gt(sum(t$amt_nominal), sum(d$amt_nominal))
-})
-
-test_that("the IG leg never includes the L-- family total", {
-  con <- .ensure_session()
-  codes <- DBI::dbGetQuery(con,
-    "SELECT DISTINCT item_code FROM ig_long")$item_code
-  expect_false(any(grepl("--$", codes)))
-  expect_true(all(substr(codes, 1, 1) %in% c("M", "L")))
-})
-
-test_that("expenditure_concept rejects unknown values", {
-  expect_error(
-    cog_spending("010000226085", years = 2019, expenditure_concept = "gross"),
-    class = "rlang_error"
-  )
-})
-
-test_that("total composes with basis = 'raw' and basis = 'harmonized'", {
-  gov <- "010000226085"
-  h <- cog_spending(gov, years = 2011, category = "Education K-12",
-                    expenditure_concept = "total", basis = "harmonized")
-  r <- cog_spending(gov, years = 2011, category = "Education K-12",
-                    expenditure_concept = "total", basis = "raw")
-  ig_h <- sum(h$amt_nominal[h$spend_subtype == "intergovernmental"])
-  ig_r <- sum(r$amt_nominal[r$spend_subtype == "intergovernmental"])
-  # The only IG harmonization rule is M38 -> M36 (year-disjoint), so the IG
-  # total must agree between bases even though the code labels may differ.
-  expect_equal(ig_h, ig_r)
-})
-
-test_that("recipe = and expenditure_concept = 'total' together aborts", {
-  expect_error(
-    cog_spending("121011212191", 2020L, recipe = "corrections_combined",
-                expenditure_concept = "total"),
-    class = "uscogdata_recipe_concept_conflict"
-  )
-})
-
-test_that("aggregate-sourced IG dollars are flagged aggregate_fallback = TRUE (bool_or, not bool_and)", {
-  # Regression test: .build_verb_sql() originally used bool_and(is_aggregate)
-  # for aggregate_fallback, which is correct for the Direct leg (a group can
-  # never mix aggregate and non-aggregate rows there -- spending_long filters
-  # NOT is_aggregate) but wrong for the IG leg. The wide era is dense -- every
-  # government has a $0 row for every code in a family -- so a $0 leaf sits in
-  # the same (year, gov, subtype, category) group as the real aggregate row
-  # and flips bool_and() to FALSE. Measured: AL state 2011 had $5,740,775,000
-  # of aggregate-sourced IG dollars (Corrections $31,358,000 + Education K-12
-  # $5,152,385,000 + General Government $557,032,000) reporting
-  # aggregate_fallback = FALSE under bool_and(), with the only TRUE row being
-  # Transit Utilities at $0. bool_or() reports all of them correctly.
-  gov <- "010000226085"
-  t <- cog_spending(gov, years = 2011, category = "Education K-12",
-                    expenditure_concept = "total")
-  ig <- t[t$spend_subtype == "intergovernmental", ]
-  expect_equal(nrow(ig), 1L)
-  expect_true(ig$aggregate_fallback)
-  expect_true(nzchar(ig$notes))
-  expect_match(ig$notes, "Aggregate fallback applied", fixed = TRUE)
-})
-
-test_that("legacy aggregate IG codes are year-disjoint from their modern leaf components", {
-  # The safety of ig_long's deliberate omission of `NOT is_aggregate` (see
-  # inst/sql/24-ig_long.sql) rests entirely on each legacy code's AGGREGATE
-  # instance being year-disjoint from the modern leaf codes it rolls up --
-  # if a future corpus rebuild ever back-filled a leaf into a year where the
-  # code is still flagged aggregate, `total` would silently double-count and
-  # this suite would still pass. This test fails loudly if that ever
-  # happens.
-  #
-  # Note the invariant is scoped to the AGGREGATE flag, not bare code
-  # presence: M89/L89 do NOT disappear after the wide era the way M47/L47
-  # do -- they continue past 2011 as their OWN independent leaf line item
-  # (is_aggregate = FALSE) alongside M91-93/L91-93, which is fine because a
-  # non-aggregate M89/L89 no longer represents a rollup of those codes.
-  # (Verified in the fixture: M89/L89 are is_aggregate = TRUE only in 2011,
-  # when M91-93/L91-93 don't exist yet; from 2012 on M89/L89 are
-  # is_aggregate = FALSE leaves coexisting with M91-93/L91-93.)
-  #
-  # Pairs are the M/L-prefixed components (this package's ig_long only
-  # covers M/L; other prefixes in the same rollup, e.g. N/O/P/Q/R, fall
-  # outside its domain and are irrelevant here) enumerated in
-  # cog_pipeline's data/wide_to_long_xwalk.csv `full_desc` column (read
-  # once at authoring time, not at test time -- this test stays offline):
-  #   M47 "To local governments, total (includes N47, O47, P47, R47, and M94)"
-  #   M89 "To local governments, total (incl N89, O89, P89, R89, M91, M92, and M93)"
-  #   L47 "To state government (includes L94)"
-  #   L89 "To state government (includes L91, L92, and L93)"
-  con <- .ensure_session()
-  pairs <- list(
-    list(aggregate = "M47", components = "M94"),
-    list(aggregate = "M89", components = c("M91", "M92", "M93")),
-    list(aggregate = "L47", components = "L94"),
-    list(aggregate = "L89", components = c("L91", "L92", "L93"))
-  )
-  agg_years_by_code <- DBI::dbGetQuery(con,
-    "SELECT DISTINCT year, item_code FROM ig_long WHERE is_aggregate")
-  codes_by_year <- DBI::dbGetQuery(con, "SELECT DISTINCT year, item_code FROM ig_long")
-
-  for (p in pairs) {
-    agg_years <- agg_years_by_code$year[agg_years_by_code$item_code == p$aggregate]
-    for (yr in agg_years) {
-      codes_yr <- codes_by_year$item_code[codes_by_year$year == yr]
-      has_component <- any(p$components %in% codes_yr)
-      expect_false(
-        has_component,
-        label = sprintf(
-          "year %s has aggregate-flagged %s co-occurring with a modern component (%s)",
-          yr, p$aggregate, paste(p$components, collapse = ",")
-        )
-      )
-    }
-  }
-})
-
-test_that(".verb_spendrev rejects expenditure_concept = 'total' for a non-spending view_base", {
-  # cog_revenue() never exposes expenditure_concept and always resolves it
-  # to the "direct" default, so there is no revenue codepath that reaches
-  # this today -- but .verb_spendrev() is shared, and nothing else stops a
-  # future caller from passing expenditure_concept = "total" alongside
-  # view_base = "revenue_annotated", which would UNION expenditure M/L rows
-  # into a revenue result. Exercise the internal helper directly.
-  expect_error(
-    uscogdata:::.verb_spendrev(
-      verb = "cog_revenue_test", view_base = "revenue_annotated",
-      subtype_col = "revenue_subtype",
-      flow_prefixes = c("T", "A", "U", "B", "C", "D"),
-      call = quote(cog_revenue_test()),
-      govid = "010000226085", years = 2019L, category = NULL,
-      per_capita = FALSE, adjust_to_year = NULL, basis = "raw",
-      recipe = NULL, expenditure_concept = "total"
-    ),
-    class = "uscogdata_expenditure_concept_unsupported"
-  )
-})
-
-test_that("cog_geographic_rollup refuses expenditure_concept = 'total'", {
-  expect_error(
-    cog_geographic_rollup(
-      govids = list(state = "010000226085"),
-      category = "Police", years = 2019,
-      expenditure_concept = "total"
-    ),
-    class = "uscogdata_concept_not_aggregatable"
-  )
-})
-
-test_that("cog_peer_compare refuses expenditure_concept = 'total'", {
-  expect_error(
-    cog_peer_compare(
-      target_govid = "010000226085", peers = "010000226085",
-      category = "Police", years = 2019,
-      expenditure_concept = "total"
-    ),
-    class = "uscogdata_concept_not_aggregatable"
-  )
-})
-
-test_that("the refusal message names the fix and the reason", {
-  err <- tryCatch(
-    cog_geographic_rollup(govids = list(state = "010000226085"),
-                          category = "Police", years = 2019,
-                          expenditure_concept = "total"),
-    condition = function(e) e
-  )
-  msg <- paste(conditionMessage(err), collapse = " ")
-  expect_match(msg, "direct")
-  expect_match(msg, "double-count|double count")
-  expect_match(msg, "cog_geographic_rollup")
-
-  # Test that cog_peer_compare's message names its own function
-  err2 <- tryCatch(
-    cog_peer_compare(target_govid = "010000226085", peers = "010000226085",
-                     category = "Police", years = 2019,
-                     expenditure_concept = "total"),
-    condition = function(e) e
-  )
-  msg2 <- paste(conditionMessage(err2), collapse = " ")
-  expect_match(msg2, "direct")
-  expect_match(msg2, "double-count|double count")
-  expect_match(msg2, "cog_peer_compare")
-})
-
-test_that("both cross-government verbs still accept the direct default", {
-  expect_no_error(
-    cog_geographic_rollup(govids = list(state = "010000226085"),
-                          category = "Police", years = 2019)
-  )
-  expect_no_error(
-    cog_peer_compare(target_govid = "010000226085", peers = "010000226085",
-                     category = "Police", years = 2019)
-  )
-})
-
-test_that("provenance always records the expenditure concept", {
-  d <- cog_spending("010000226085", years = 2019, category = "Police")
-  t <- cog_spending("010000226085", years = 2019, category = "Police",
-                    expenditure_concept = "total")
-  expect_equal(attr(d, "provenance")$expenditure_concept, "direct")
-  expect_equal(attr(t, "provenance")$expenditure_concept, "total")
-  # The note explains the non-obvious part: how legacy IG was assembled.
-  expect_true(nzchar(attr(t, "provenance")$expenditure_concept_note))
-  expect_true(is.na(attr(d, "provenance")$expenditure_concept_note) ||
-              !nzchar(attr(d, "provenance")$expenditure_concept_note))
-})
-
-test_that("the provenance schema documents expenditure_concept", {
-  sch <- jsonlite::fromJSON(
-    system.file("schemas", "provenance-v1.json", package = "uscogdata"),
-    simplifyVector = FALSE
-  )
-  expect_true("expenditure_concept" %in% names(sch$properties))
-})
-
-test_that("a firing suggestion names the intergovernmental counterpart recipe", {
-  # Corrections has no legacy leaf rows, so the coverage-gap suggestion fires;
-  # corrections_ig_local_combined is its IG counterpart.
-  r <- suppressMessages(
-    cog_spending("010000226085", years = c(2005, 2011), category = "Corrections")
-  )
-  sugg <- attr(r, "provenance")$suggestions
-  expect_gt(length(sugg), 0L)
-  ids <- vapply(sugg, function(s) s$recipe_id %||% "", character(1))
-  expect_true("corrections_combined" %in% ids)
-  ig <- unlist(lapply(sugg, function(s) s$ig_recipe_id))
-  expect_true("corrections_ig_local_combined" %in% ig)
-})
-
-test_that("no suggestion fires for a healthy query", {
-  r <- cog_spending("010000226085", years = 2019, category = "Police")
-  expect_length(attr(r, "provenance")$suggestions, 0L)
-})
-
-test_that("a mis-scoped cog_spending() call never attaches an M/L counterpart to a revenue-flavored recipe", {
-  # "IG Federal" is a revenue-only category (summary_categories maps it to
-  # B-prefixed component codes only; its recipes are ig_federal_b47_wide /
-  # ig_federal_b89_wide). A cog_spending() call scoped to it returns zero
-  # spending rows for every requested year -- there is no spending
-  # component in this category at all -- so the coverage-gap machinery
-  # fires for real (not hypothetically) even though this isn't the kind of
-  # format-boundary gap the recipe catalog is meant to signpost. This is
-  # exactly the live-corpus risk flagged in review: ig_federal_b47_wide's
-  # own component codes (B47/B94, suffixes {"47","94"}) are an EXACT
-  # suffix-set match for the expenditure recipe ige_local_m47_wide
-  # (M47/M94, same suffixes) -- a coincidence of reused digits, not a real
-  # Direct/Total pairing. The flow-family gate in
-  # .attach_ig_counterparts() must keep ig_recipe_id NULL here.
-  r <- suppressMessages(
-    cog_spending("010000226085", years = c(2005, 2011), category = "IG Federal")
-  )
-  sugg <- attr(r, "provenance")$suggestions
-  expect_gt(length(sugg), 0L)
-  ids <- vapply(sugg, function(s) s$recipe_id %||% "", character(1))
-  expect_true("ig_federal_b47_wide" %in% ids)
-  ig <- unlist(lapply(sugg, function(s) s$ig_recipe_id))
-  expect_length(ig, 0L)
-})
-
-test_that("C1: 'total' on a legacy aggregate-only family reports the IG-only figure honestly, not as Direct + IG", {
-  # AL state government, Corrections, 2011. Measured pre-fix: 'total'
-  # returned $31,358,000 (the IG leg alone, on an aggregate-flagged M04/M05
-  # row) with 0 suggestions (the surviving IG row made the gap-detection
-  # machinery think the Direct leg was covered) and a note asserting
-  # "Total = Direct + intergovernmental" with no caveat. True Direct (via
-  # recipe = "corrections_combined") is $521,651,000 -- the IG-only figure
-  # is ~6% of it.
-  gov <- "010000226085"
-
-  d <- cog_spending(gov, years = 2011, category = "Corrections",
-                    expenditure_concept = "direct")
-  expect_equal(nrow(d), 0L)
-
-  t <- suppressMessages(cog_spending(
-    gov, years = 2011, category = "Corrections", expenditure_concept = "total"
-  ))
-  expect_equal(nrow(t), 1L)
-  expect_equal(t$spend_subtype, "intergovernmental")
-  expect_equal(t$amt_nominal, 31358000)
-
-  r <- cog_spending(gov, years = 2011, recipe = "corrections_combined")
-  expect_equal(r$amt_nominal, 521651000)
-
-  # C1(a): the recipe hints must fire for "total" exactly as they do for
-  # "direct" -- the surviving IG row must not be mistaken for Direct
-  # coverage.
-  prov <- attr(t, "provenance")
-  expect_gt(length(prov$suggestions), 0L)
-  ids <- vapply(prov$suggestions, function(s) s$recipe_id %||% "", character(1))
-  expect_true("corrections_combined" %in% ids)
-
-  # C1(b): the affected row's notes name a recovering recipe rather than
-  # staying silent, and the provenance carries a flag a downstream consumer
-  # (e.g. cog-api, which passes provenance through verbatim) can test.
-  expect_true(nzchar(t$notes))
-  expect_match(t$notes, "unavailable", fixed = TRUE)
-  expect_match(t$notes, "corrections_combined", fixed = TRUE)
-  expect_true(prov$expenditure_concept_direct_suppressed)
-
-  # The base "Total = Direct + IG" note must NOT stand unqualified when that
-  # arithmetic didn't actually happen for this row.
-  expect_match(prov$expenditure_concept_note, "NOTE", fixed = TRUE)
-  expect_match(prov$expenditure_concept_note,
-              "expenditure_concept_direct_suppressed", fixed = TRUE)
-})
-
-test_that("C1(b): expenditure_concept_direct_suppressed is FALSE when the Direct leg is present", {
-  d <- cog_spending("010000226085", years = 2019, category = "Police",
-                    expenditure_concept = "direct")
-  t <- cog_spending("010000226085", years = 2019, category = "Police",
-                    expenditure_concept = "total")
-  expect_false(isTRUE(attr(d, "provenance")$expenditure_concept_direct_suppressed))
-  expect_false(isTRUE(attr(t, "provenance")$expenditure_concept_direct_suppressed))
-  expect_false(any(nzchar(t$notes[t$spend_subtype == "intergovernmental"]) &
-                   grepl("unavailable", t$notes[t$spend_subtype == "intergovernmental"])))
-})
-
-# M/I fix: .detect_direct_suppressed() was equating "no Direct sibling row"
-# with "Direct was suppressed", but the dominant real cause is a government
-# that simply has no direct spending in that category -- correct, ordinary
-# data. The fix gates the flag (and its row note) on a harmonization recipe
-# ACTUALLY covering that exact (year, canonical_govid, category) triple.
-
-test_that("M/I: true positive, category supplied explicitly (unchanged behavior)", {
-  al <- "010000226085"
-  t_cat <- suppressMessages(cog_spending(
-    al, years = 2011, category = "Corrections", expenditure_concept = "total"
-  ))
-  expect_true(attr(t_cat, "provenance")$expenditure_concept_direct_suppressed)
-  expect_match(t_cat$notes, "corrections_combined", fixed = TRUE)
-  expect_match(t_cat$notes, "unavailable", fixed = TRUE)
-})
-
-test_that("M/I: true positive, category = NULL now also names the recipe (was the fallback bug)", {
-  # Root bug: .build_suggestions() short-circuits to list() when category is
-  # NULL, so the note previously always hit its "no covering recipe found"
-  # fallback here even though corrections_combined genuinely covers this row.
-  al <- "010000226085"
-  t_null <- suppressMessages(cog_spending(
-    al, years = 2011, category = NULL, expenditure_concept = "total"
-  ))
-  corr_row <- t_null[t_null$category %in% "Corrections", ]
-  expect_equal(nrow(corr_row), 1L)
-  expect_true(attr(t_null, "provenance")$expenditure_concept_direct_suppressed)
-  expect_match(corr_row$notes, "corrections_combined", fixed = TRUE)
-  expect_match(corr_row$notes, "unavailable", fixed = TRUE)
-  expect_false(grepl("no covering recipe found", corr_row$notes, fixed = TRUE))
-})
-
-test_that("M/I: false positive -- Virginia Education K-12 FY2019 total is NOT flagged", {
-  # States fund K-12 through school districts, so the Direct leg (E12/F12/
-  # G12) is genuinely, correctly zero -- not suppressed. Must not be flagged
-  # and must carry no suppression note.
-  va <- "510000227542"
-  t_va <- suppressMessages(cog_spending(
-    va, years = 2019, category = "Education K-12", expenditure_concept = "total"
-  ))
-  expect_equal(nrow(t_va), 1L)
-  expect_equal(t_va$spend_subtype, "intergovernmental")
-  expect_equal(t_va$amt_nominal, 8028179000)
-  expect_false(isTRUE(attr(t_va, "provenance")$expenditure_concept_direct_suppressed))
-  expect_false(nzchar(t_va$notes) && grepl("unavailable", t_va$notes))
-})
-
-test_that("M/I: false positive by construction -- 'Other Education' has no E/F/G code, never flagged", {
-  # "Other Education" maps only to M21/L21 in summary_categories -- there is
-  # no E/F/G code for it in this corpus at all, so no Direct-recovering
-  # recipe can exist and it must never be flagged, in any fixture year.
-  con <- uscogdata:::.ensure_session()
-  years_all <- DBI::dbGetQuery(con, "SELECT DISTINCT year FROM long ORDER BY year")$year
-  states <- DBI::dbGetQuery(con,
-    "SELECT DISTINCT canonical_govid FROM long WHERE type = 0")$canonical_govid
-  oe <- suppressMessages(cog_spending(
-    states, years = years_all, category = "Other Education",
-    expenditure_concept = "total"
-  ))
-  expect_false(isTRUE(attr(oe, "provenance")$expenditure_concept_direct_suppressed))
-  expect_false(any(nzchar(oe$notes) & grepl("unavailable", oe$notes)))
-})
-
-test_that("M/I: a clean FY2019 category = NULL total query flags far fewer than the pre-fix 32/50 states", {
-  con <- uscogdata:::.ensure_session()
-  states <- DBI::dbGetQuery(con,
-    "SELECT DISTINCT canonical_govid FROM long WHERE type = 0")$canonical_govid
-  r <- suppressMessages(cog_spending(
-    states, years = 2019, category = NULL, expenditure_concept = "total"
-  ))
-  ig <- r[r$spend_subtype == "intergovernmental", ]
-  flagged <- ig[nzchar(ig$notes) & grepl("unavailable", ig$notes), ]
-  expect_lt(length(unique(flagged$canonical_govid)), 32L)
-  # Every remaining flagged row must actually name a covering recipe --
-  # never the old no-recipe-found fallback.
-  expect_true(all(grepl("recipe = '", flagged$notes, fixed = TRUE)))
-  expect_false(any(grepl("no covering recipe found", flagged$notes, fixed = TRUE)))
-})
-
-test_that("C2: expenditure_concept = 'total' aborts on a corpus with no intergovernmental category rows", {
-  with_corpus_missing_ig_categories({
-    con <- uscogdata:::.ensure_session()
-    n <- DBI::dbGetQuery(con,
-      "SELECT COUNT(*) AS n FROM summary_categories WHERE LEFT(item_code, 1) IN ('M', 'L')"
-    )$n
-    expect_equal(n, 0)
-
-    err <- tryCatch(
-      cog_spending("010000226085", years = 2019, category = "Police",
-                  expenditure_concept = "total"),
-      condition = function(e) e
-    )
-    expect_s3_class(err, "uscogdata_ig_categories_unsupported")
-    msg <- conditionMessage(err)
-    expect_match(msg, "PR #59|predates", perl = TRUE)
-  })
-
-  # 'direct' is unaffected on the same corpus -- the guard is scoped to
-  # expenditure_concept = "total" only.
-  with_corpus_missing_ig_categories({
-    expect_no_error(
-      cog_spending("010000226085", years = 2019, category = "Police",
-                  expenditure_concept = "direct")
-    )
-  })
-})
-
-test_that("C2: expenditure_concept = 'total' still works on a corpus that DOES carry M/L category rows", {
-  expect_no_error(
-    cog_spending("010000226085", years = 2019, category = "Police",
-                expenditure_concept = "total")
-  )
-})
-
-test_that("I2: an intergovernmental (M/L) recipe never appears as its own top-level suggestion", {
-  # Task 1's M04/M05 category rows share the "Corrections" summary_categories
-  # category with the Direct-flavored E04/E05, so `corrections_ig_local_
-  # combined` (entirely M-prefixed) becomes a raw *candidate* in
-  # .build_suggestions()'s component_code-driven query. Following a
-  # "re-run with recipe = 'corrections_ig_local_combined'" hint on a plain
-  # cog_spending() call would silently return intergovernmental dollars
-  # under provenance$expenditure_concept = "direct". Task 6's gate
-  # (.attach_ig_counterparts()) already protects the *counterpart* lookup;
-  # this exercises that the candidate list itself is filtered too.
-  r <- suppressMessages(
-    cog_spending("010000226085", years = c(2005, 2011), category = "Corrections")
-  )
-  sugg <- attr(r, "provenance")$suggestions
-  ids <- vapply(sugg, function(s) s$recipe_id %||% "", character(1))
-  expect_true("corrections_combined" %in% ids)
-  expect_false("corrections_ig_local_combined" %in% ids)
-})
-
-test_that(".attach_ig_counterparts() never pairs a revenue-side recipe with its coincidental M/L suffix twin", {
-  # Broader version of the case above, run at the matching-helper level
-  # (the same level code review's pairwise enumeration was done at) rather
-  # than end-to-end: the fixture has no (govid, year) combination where
-  # cog_revenue() itself produces a covered gap for any B/C/D recipe, so an
-  # end-to-end repro for THIS specific set of recipes isn't reachable
-  # today. Each of these six recipes shares an exact suffix set with an
-  # M/L expenditure recipe purely by reused-digit coincidence:
-  #   ig_federal_b47_wide {"47","94"} == ige_local_m47_wide / ige_state_l47_wide
-  #   ig_federal_b89_wide {"89","91","92","93"} == ige_local_m89_wide / ige_state_l89_wide
-  #   ig_state_c47_wide   {"47","94"} == ige_local_m47_wide / ige_state_l47_wide
-  #   ig_state_c89_wide   {"89","91","92","93"} == ige_local_m89_wide / ige_state_l89_wide
-  #   ig_local_d47_wide   {"47","94"} == ige_local_m47_wide / ige_state_l47_wide
-  #   ig_local_d89_wide   {"89","91","92","93"} == ige_local_m89_wide / ige_state_l89_wide
-  # None of them may receive an ig_recipe_id under cog_revenue()'s own
-  # flow_prefixes, since M/L only ever pairs with the direct-expenditure
-  # (E/F/G) family.
-  con <- uscogdata:::.ensure_session()
-  fake_suggestion <- function(rid) {
-    list(recipe_id = rid, label = "x", available_years = c(1967L, 2023L),
-         hint = "h")
-  }
-  fake_suggestions <- lapply(
-    c("ig_federal_b47_wide", "ig_federal_b89_wide",
-      "ig_state_c47_wide", "ig_state_c89_wide",
-      "ig_local_d47_wide", "ig_local_d89_wide"),
-    fake_suggestion
-  )
-  out <- uscogdata:::.attach_ig_counterparts(
-    con, fake_suggestions, c("T", "A", "U", "B", "C", "D")
-  )
-  ig <- unlist(lapply(out, function(s) s$ig_recipe_id))
-  expect_length(ig, 0L)
-})

tests/testthat/test-explain.R

@@ -70,37 +70,6 @@ test_that("cog_explain prints a Suggestions section when the provenance has one"
   expect_true(grepl("re-run with recipe", txt))
 })
 
-test_that("cog_explain prints the expenditure concept (I1)", {
-  skip_if_no_corpus()
-  d <- cog_spending("010000226085", years = 2019, category = "Police")
-  t <- cog_spending("010000226085", years = 2019, category = "Police",
-                    expenditure_concept = "total")
-  txt_d <- paste(c(
-    capture.output(cog_explain(d)),
-    capture.output(cog_explain(d), type = "message")
-  ), collapse = "\n")
-  txt_t <- paste(c(
-    capture.output(cog_explain(t)),
-    capture.output(cog_explain(t), type = "message")
-  ), collapse = "\n")
-  expect_true(grepl("Concept: direct", txt_d))
-  expect_true(grepl("Concept: total", txt_t))
-})
-
-test_that("cog_explain surfaces the C1(b) direct-suppressed flag as a warning", {
-  skip_if_no_corpus()
-  t <- suppressMessages(cog_spending(
-    "010000226085", years = 2011, category = "Corrections",
-    expenditure_concept = "total"
-  ))
-  expect_true(attr(t, "provenance")$expenditure_concept_direct_suppressed)
-  txt <- paste(c(
-    capture.output(cog_explain(t)),
-    capture.output(cog_explain(t), type = "message")
-  ), collapse = "\n")
-  expect_true(grepl("Direct leg unavailable", txt))
-})
-
 test_that("cog_explain prints denominator + popyear_range + counts", {
   skip_if_no_corpus()
   with_fixture_corpus({

tests/testthat/test-recipes.R

@@ -176,6 +176,16 @@ test_that("recipe = requires schema_version >= 5", {
 })
 
 # --- signposting -------------------------------------------------------
+#
+# Phase R3 / Task 19c: .build_suggestions() was narrowed from a whole-result
+# gap check (R2: does the ENTIRE category result have zero rows in a
+# requested year) to per-code gap detection (does a specific recipe
+# component -- itself a member of the requested category -- have zero rows
+# in a year the recipe's own generic join otherwise covers). See
+# R/suggestions.R's header comment and docs/phase_r_harmonization_review.md
+# § 0.3. The R2 test below ("...across the 2011->2012 gap") is unaffected
+# by the refinement (it already passed under both the coarse and per-code
+# rule). The next few pin cases the coarse rule specifically could NOT see.
 
 test_that("signposting suggests corrections_combined across the 2011->2012 gap", {
   skip_if_no_corpus()
@@ -193,10 +203,96 @@ test_that("signposting suggests corrections_combined across the 2011->2012 gap",
   expect_equal(hit$available_years, c(1967L, 2023L))
 })
 
-test_that("no signposting when the result already has full year coverage", {
+test_that("per-code gap does NOT fire when a code's only coverage is its own aggregate row (self-coverage is not \"other components\")", {
   skip_if_no_corpus()
+  # Broward, FY2011 ONLY (isolating the 2011 half of the query above): E05,
+  # F05, and G05 each report SOLELY as a wide-era AGGREGATE row that year
+  # (216088, 1453, 270 respectively); E04/F04/G04 -- their modern-only
+  # siblings -- don't exist as codes at all before 2012, corpus-wide (zero
+  # rows for any government). Each component's own aggregate row would
+  # trivially satisfy a same-component "covered" check, but review-doc
+  # § 0.3's criterion is explicit that a gap must be covered by "OTHER
+  # components", not the gapped component's own aggregate form. With no
+  # OTHER component present for any of the three Corrections recipes in
+  # 2011, none of them should fire -- this is what the combined
+  # 2011-2012 test above actually relies on 2012 (E05 gapped, E04 -- a
+  # genuinely different component -- covers) to fire, not 2011.
+  r <- cog_spending("121011212191", years = 2011L, category = "Corrections")
+  prov <- attr(r, "provenance")
+  expect_length(prov$suggestions, 0L)
+})
+
+test_that("per-code gap fires even when a sibling code masks the whole-result check (Cleburne County, FY2012)", {
+  skip_if_no_corpus()
+  # Cleburne County, AL (canonical_govid 011029122489), FY2012: E04 ($854)
+  # and E05 ($1) both report ("operations" subtype), and G04 ($14,000,
+  # corrections_other_capital_combined's modern-only leg) also reports
+  # ("capital" subtype) -- so the WHOLE category result is non-empty for
+  # 2012 (2 rows) and the R2 whole-result check would never look further.
+  # But G05 -- G04's OWN recipe sibling, the 1967-2023 wide leg -- has
+  # ZERO rows at all that year: a genuine, per-code gap the recipe exists
+  # to bridge, invisible at the category-result grain because it's masked
+  # by G04's own data, let alone the unrelated E04/E05 pair.
+  r <- cog_spending("011029122489", years = 2012L, category = "Corrections")
+  expect_equal(nrow(r), 2L)  # operations + capital rows: a non-empty result
+
+  prov <- attr(r, "provenance")
+  ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
+  expect_true("corrections_other_capital_combined" %in% ids)
+  hit <- prov$suggestions[[which(ids == "corrections_other_capital_combined")]]
+  expect_equal(hit$hint, "re-run with recipe = 'corrections_other_capital_combined'")
+  expect_equal(hit$available_years, c(1967L, 2023L))
+
+  # corrections_combined must NOT fire: E04 AND E05 both have real 2012
+  # data for this government, so neither of ITS OWN components is gapped.
+  expect_false("corrections_combined" %in% ids)
+})
+
+test_that("per-code gap does not fire when no recipe component has any data at all (ordinary reporting variance, not a format-boundary gap)", {
+  skip_if_no_corpus()
+  # Same government/year as above: F04 and F05 (corrections_capital_combined)
+  # are BOTH completely absent -- Cleburne simply never reported capital
+  # corrections spending under that code family in 2012, wide-era or
+  # modern. The recipe's own generic join (aggregate-inclusive, either
+  # component) has nothing to offer either, so this must stay silent --
+  # the per-government `covered` guard the header comment describes is
+  # unchanged and still does this filtering.
+  r <- cog_spending("011029122489", years = 2012L, category = "Corrections")
+  prov <- attr(r, "provenance")
+  ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
+  expect_false("corrections_capital_combined" %in% ids)
+})
+
+test_that("per-code gap fires for Broward 2019-2020 even though the category result looks complete", {
+  skip_if_no_corpus()
+  # Broward reports E04 + G04 (modern leaf codes) in BOTH 2019 and 2020 but
+  # never reports E05 or G05 (their own recipe siblings) in either year --
+  # a real per-code gap in two of the three Corrections recipes, invisible
+  # under the R2 coarse check because the category *result* is non-empty
+  # both years (this replaces the old R2-era "full year coverage" test,
+  # whose premise -- that a non-empty result implies nothing to signpost --
+  # is exactly what this refinement narrows; see data-raw/
+  # measure_signposting_rate.R for the measured rate change this causes).
+  # corrections_capital_combined correctly stays silent: Broward reports
+  # neither F04 nor F05 in 2019 or 2020, so that recipe's own join has
+  # nothing to offer either (ordinary non-reporting, not a format-boundary
+  # gap) -- the per-government `covered` guard still does its job here too.
   r <- cog_spending("121011212191", years = 2019:2020, category = "Corrections")
   prov <- attr(r, "provenance")
+  ids <- vapply(prov$suggestions, function(s) s$recipe_id, character(1))
+  expect_true("corrections_combined" %in% ids)
+  expect_true("corrections_other_capital_combined" %in% ids)
+  expect_false("corrections_capital_combined" %in% ids)
+})
+
+test_that("no signposting when every recipe component genuinely has data (true full per-code coverage)", {
+  skip_if_no_corpus()
+  # Maricopa County, AZ (canonical_govid 041013160815): all six Corrections
+  # codes (E04, E05, F04, F05, G04, G05) report real, nonzero, non-aggregate
+  # amounts in BOTH 2019 and 2020 -- genuinely nothing for any recipe to
+  # fill, even at the finer per-code grain this refinement now checks.
+  r <- cog_spending("041013160815", years = 2019:2020, category = "Corrections")
+  prov <- attr(r, "provenance")
   expect_length(prov$suggestions, 0L)
 })
 

tests/testthat/test-signposting-harness.R

@@ -0,0 +1,164 @@
+# tests/testthat/test-signposting-harness.R
+#
+# Pins the subset-relation REPORTING in data-raw/measure_signposting_rate.R.
+#
+# Phase R3 Task 19c narrowed signposting from a coarse whole-result gap
+# check to per-code gap detection. Those two checks are partly DISJOINT,
+# not nested: a query can fire under coarse and stay silent under per-code,
+# so the harness's `*_delta_pp` figures are NETS that can hide a coverage
+# loss. `.measure_subset_relation()` is what separates the two flows, and
+# `.measure_format_subset_report()` is what puts the loss in front of a
+# human. Both are load-bearing for the Checkpoint R3 ruling, so both are
+# pinned here: if the violation detection is deleted, inverted, or quietly
+# downgraded to a count with no identities, these tests fail.
+#
+# These tests do NOT assert that the violation set is empty -- it is
+# genuinely non-empty, and asserting otherwise would be pinning a bug as a
+# contract. They assert only that a real violation is DETECTED and NAMED.
+
+# The harness lives in data-raw/, which is .Rbuildignore'd, so it is absent
+# from an installed/checked tarball. Source it into an env parented on the
+# namespace so it resolves the package internals it calls (.build_verb_sql,
+# .build_suggestions) exactly as it does when run for real.
+harness_env <- function() {
+  path <- testthat::test_path("..", "..", "data-raw", "measure_signposting_rate.R")
+  skip_if_not(file.exists(path),
+              "data-raw/ is .Rbuildignore'd; harness not present in this tree")
+  env <- new.env(parent = asNamespace("uscogdata"))
+  source(path, local = env)
+  env
+}
+
+# A detail frame in exactly the shape .measure_one_query() emits, covering
+# all four quadrants of the coarse x percode cross-tab.
+fake_detail <- function() {
+  data.frame(
+    category         = c("Corrections", "Other Taxes", "Police", "Fire"),
+    category_type    = c("expenditure", "revenue", "expenditure", "expenditure"),
+    canonical_govid  = c("121011212191", "472155175824", "011029122489",
+                         "041013160815"),
+    n_result_rows    = c(0L, 1L, 2L, 6L),
+    coarse_gap_years = c("2011", "", "", ""),
+    fired_coarse     = c(TRUE, FALSE, TRUE, FALSE),
+    fired_percode    = c(FALSE, TRUE, TRUE, FALSE),
+    coarse_recipes   = c("corrections_combined", "", "police_combined", ""),
+    percode_recipes  = c("", "t29_license_wide", "police_combined", ""),
+    stringsAsFactors = FALSE
+  )
+}
+
+test_that(".measure_subset_relation() separates coverage LOST from coverage ADDED", {
+  e   <- harness_env()
+  rel <- e$.measure_subset_relation(fake_detail())
+
+  # Row 1 (coarse fired, per-code silent) is the violation; row 2 is the
+  # addition; row 3 agrees; row 4 is silent.
+  expect_false(rel$holds)
+  expect_equal(rel$n_violations, 1L)
+  expect_equal(rel$n_additions, 1L)
+  expect_equal(rel$n_coarse_fired, 2L)
+  expect_equal(rel$n_percode_fired, 2L)
+  expect_equal(rel$n_both, 1L)
+  expect_equal(rel$n_queries, 4L)
+
+  # The violation must be NAMED down to (category, government, year), not
+  # merely counted -- that is what makes it inspectable at Checkpoint R3.
+  expect_equal(rel$violations$category, "Corrections")
+  expect_equal(rel$violations$canonical_govid, "121011212191")
+  expect_equal(rel$violations$coarse_gap_years, "2011")
+  expect_equal(rel$violations$coarse_recipes, "corrections_combined")
+
+  # Inversion guard: an implementation that swapped the two directions
+  # would report the addition as a violation and vice versa.
+  expect_false("Other Taxes" %in% rel$violations$category)
+  expect_equal(rel$additions$category, "Other Taxes")
+  expect_false("Corrections" %in% rel$additions$category)
+
+  # Agreeing and silent queries belong to neither set.
+  expect_false("Police" %in% c(rel$violations$category, rel$additions$category))
+  expect_false("Fire" %in% c(rel$violations$category, rel$additions$category))
+})
+
+test_that(".measure_subset_relation() reports holds = TRUE only when nothing fires coarse-only", {
+  e <- harness_env()
+  # Drop the violating row: coarse is now genuinely a subset of per-code.
+  clean <- fake_detail()[-1L, , drop = FALSE]
+  rel   <- e$.measure_subset_relation(clean)
+
+  expect_true(rel$holds)
+  expect_equal(rel$n_violations, 0L)
+  expect_equal(nrow(rel$violations), 0L)
+  expect_equal(rel$n_additions, 1L)
+})
+
+test_that(".measure_subset_relation() validates its input rather than silently mis-reporting", {
+  e <- harness_env()
+  expect_error(e$.measure_subset_relation("not a data frame"), "must be a data frame")
+  expect_error(e$.measure_subset_relation(fake_detail()[, c("category", "canonical_govid")]),
+               "fired_coarse")
+  bad <- fake_detail()
+  bad$fired_percode[1] <- NA
+  expect_error(e$.measure_subset_relation(bad), "non-NA logicals")
+})
+
+test_that("the subset report NAMES a coarse-only firing as a violation", {
+  e   <- harness_env()
+  txt <- paste(e$.measure_format_subset_report(e$.measure_subset_relation(fake_detail())),
+               collapse = "\n")
+
+  # Stated plainly as a violation, not buried.
+  expect_match(txt, "VIOLATED")
+  expect_match(txt, "COVERAGE LOST")
+  expect_no_match(txt, "HOLDS")
+  # ...and the offending query named, so a human can go look at it.
+  expect_match(txt, "Corrections")
+  expect_match(txt, "121011212191")
+  expect_match(txt, "2011")
+  # ...and the delta explicitly flagged as a net of both directions.
+  expect_match(txt, "NET")
+})
+
+test_that("the subset report says HOLDS when coarse really is a subset", {
+  e   <- harness_env()
+  rel <- e$.measure_subset_relation(fake_detail()[-1L, , drop = FALSE])
+  txt <- paste(e$.measure_format_subset_report(rel), collapse = "\n")
+
+  expect_match(txt, "HOLDS")
+  expect_no_match(txt, "VIOLATED")
+  expect_no_match(txt, "COVERAGE LOST")
+})
+
+test_that("a REAL coarse-fires/per-code-silent query is measured and reported as a violation", {
+  skip_if_no_corpus()
+  # Broward County FY2011, Corrections: E05/F05/G05 report SOLELY as
+  # wide-era aggregate rows, which basis = "harmonized" excludes, so the
+  # whole category result is empty -- coarse's trigger. Their modern-only
+  # siblings E04/F04/G04 do not exist as codes at all before 2012, so no
+  # OTHER component can supply per-code's covering evidence and per-code
+  # is structurally unable to fire. This is the disjointness the harness
+  # exists to surface, measured end-to-end through the real git-loaded
+  # coarse arm and the live per-code arm (not a hand-built frame).
+  e   <- harness_env()
+  con <- uscogdata:::cog_open()
+  row <- e$.measure_one_query(
+    con,
+    coarse_env  = e$.measure_load_git_impl("b0df1ec"),
+    selfcov_env = e$.measure_load_git_impl("da72bf3"),
+    category = "Corrections", category_type = "expenditure",
+    govid = "121011212191", years = 2011L
+  )
+
+  expect_true(row$fired_coarse)
+  expect_false(row$fired_percode)
+  expect_equal(row$n_result_rows, 0L)
+  expect_equal(row$coarse_gap_years, "2011")
+
+  rel <- e$.measure_subset_relation(row)
+  expect_false(rel$holds)
+  expect_equal(rel$n_violations, 1L)
+  expect_equal(rel$violations$canonical_govid, "121011212191")
+
+  txt <- paste(e$.measure_format_subset_report(rel), collapse = "\n")
+  expect_match(txt, "VIOLATED")
+  expect_match(txt, "121011212191")
+})

tests/testthat/test-views.R

@@ -9,9 +9,7 @@ test_that("all expected views register on session open", {
   expected <- c(
     "long", "spending_long", "revenue_long",
     "canonical_fips_xwalk", "summary_categories",
-    "spending_annotated", "revenue_annotated",
-    "ig_long", "ig_annotated",
-    "ig_long_harmonized", "ig_annotated_harmonized"
+    "spending_annotated", "revenue_annotated"
   )
   expect_true(all(expected %in% views$table_name))
 })
@@ -112,70 +110,6 @@ test_that("inst/sql/22- and 23- harmonized views enforce every WHERE predicate (
   expect_equal(rev$amt, 225)
 })
 
-test_that("inst/sql/24- and 25- IG views retain aggregates, COALESCE NULL harmonized_code, and exclude the L-- family total (real SQL text, synthetic parquet)", {
-  # ig_long / ig_long_harmonized have the subtlest predicates in the package:
-  # a deliberately ABSENT `NOT is_aggregate` (unlike every other *_long view),
-  # and COALESCE(harmonized_code, item_code) instead of a plain
-  # `harmonized_code IS NOT NULL` filter. The only end-to-end guard on this
-  # today is bound to AL state / 2011 / Education K-12, where M12 happens to
-  # be the sole IG code present -- regenerate the fixture without that one
-  # row and the guard would die silently while staying green. As with the
-  # 22-/23- test above, this reads the real inst/sql/24-/25- text off disk
-  # and executes it against a synthetic hive-partitioned parquet tree, so a
-  # regression in either predicate changes which rows survive.
-  skip_if_no_corpus()
-
-  tmp <- withr::local_tempdir()
-  part_dir <- file.path(tmp, "data", "long", "year=2004")
-  dir.create(part_dir, recursive = TRUE)
-  part_path <- file.path(part_dir, "part-0.parquet")
-
-  write_con <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(write_con, shutdown = TRUE), add = TRUE)
-  DBI::dbExecute(write_con, sprintf("
-    COPY (
-      SELECT * FROM (VALUES
-        ('ig-A', 'M04', 100,   false, 'M04'), -- control: passes through as-is
-        ('ig-B', 'M38', 50,    false, 'M36'), -- fold control: real SB012 rule, renamed to M36 under harmonized basis
-        ('ig-C', 'M47', 99999, true,  NULL),  -- legacy aggregate, NO harmonized_code: must survive BOTH views
-        ('ig-D', 'L--', 55555, false, 'L--'), -- family total: excluded from BOTH views
-        ('ig-E', 'T29', 44444, false, 'T29')  -- wrong prefix (revenue, not M/L): excluded from BOTH views
-      ) AS t(canonical_govid, item_code, amt, is_aggregate, harmonized_code)
-    ) TO %s (FORMAT PARQUET)
-  ", uscogdata:::.sql_lit_chr(part_path)))
-
-  sql_dir <- system.file("sql", package = "uscogdata")
-  .read_view_sql <- function(filename) {
-    txt <- paste(readLines(file.path(sql_dir, filename), warn = FALSE), collapse = "\n")
-    gsub("\\{url\\}", paste0(tmp, "/"), txt, fixed = FALSE)
-  }
-
-  con <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(con, shutdown = TRUE), add = TRUE)
-  DBI::dbExecute(con, .read_view_sql("10-long.sql"))
-  DBI::dbExecute(con, .read_view_sql("24-ig_long.sql"))
-  DBI::dbExecute(con, .read_view_sql("25-ig_long_harmonized.sql"))
-
-  raw <- DBI::dbGetQuery(con,
-    "SELECT item_code, SUM(amt) AS amt FROM ig_long
-     GROUP BY item_code ORDER BY item_code"
-  )
-  # L-- (family total) and T29 (wrong prefix) are gone; the aggregate row
-  # M47 survives -- proof `NOT is_aggregate` is absent from ig_long.
-  expect_equal(raw$item_code, c("M04", "M38", "M47"))
-  expect_equal(raw$amt, c(100, 50, 99999))
-
-  harmonized <- DBI::dbGetQuery(con,
-    "SELECT item_code, SUM(amt) AS amt FROM ig_long_harmonized
-     GROUP BY item_code ORDER BY item_code"
-  )
-  # M38 folds to M36 (real harmonized_code present); M47 keeps its raw code
-  # via COALESCE(NULL, 'M47') -- proof the aggregate row is NOT dropped by
-  # a plain `harmonized_code IS NOT NULL` filter. L-- and T29 stay excluded.
-  expect_equal(harmonized$item_code, c("M04", "M36", "M47"))
-  expect_equal(harmonized$amt, c(100, 50, 99999))
-})
-
 test_that(".build_series_break_refs matches fin_code + break_year window", {
   # No series_breaks_pq row falls inside the bundled fixture's 2011-2020
   # window (data-verified; see the "series_break_refs" test in
@@ -218,108 +152,6 @@ test_that("schema v5 harmonization views register when the corpus supports them"
   expect_true(all(expected_v5 %in% views$table_name))
 })
 
-test_that(".harmonization_view_files guard is necessary: registration against a v4-shaped corpus (no harmonized_code column at all) succeeds only because the harmonized views are skipped", {
-  # with_doctored_schema_version() (used elsewhere in this suite) only
-  # rewrites manifest.json's schema_version -- the underlying `long` parquet
-  # is still the bundled v6 fixture, which DOES have a harmonized_code
-  # column, so it only proves the skip *happens*, not that it is *required*.
-  # This test builds a genuinely v4-shaped corpus: `long` has no
-  # harmonized_code column at all, matching a real pre-Phase-R2 publish
-  # tree, and then shows two things: (1) the real .register_views(), gated
-  # on manifest$schema_version, registers cleanly against it; (2) the exact
-  # SQL text of a gated file (25-ig_long_harmonized.sql), executed directly
-  # against the same corpus without the gate, fails -- proving the gate is
-  # load-bearing, not incidental.
-  tmp <- withr::local_tempdir()
-  part_dir <- file.path(tmp, "data", "long", "year=2004")
-  dir.create(part_dir, recursive = TRUE)
-  part_path <- file.path(part_dir, "part-0.parquet")
-
-  write_con <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(write_con, shutdown = TRUE), add = TRUE)
-  DBI::dbExecute(write_con, sprintf("
-    COPY (
-      SELECT * FROM (VALUES
-        ('gov-1', 'E36', 100, false, 500000, 2020)
-      ) AS t(canonical_govid, item_code, amt, is_aggregate, population, popyear)
-    ) TO %s (FORMAT PARQUET)
-  ", uscogdata:::.sql_lit_chr(part_path)))
-
-  xwalk_path <- file.path(tmp, "data", "canonical_fips_xwalk.parquet")
-  DBI::dbExecute(write_con, sprintf("
-    COPY (
-      SELECT * FROM (VALUES
-        ('gov-1', 'Test Gov', 1, 'County', '01', '001', NULL, 500000)
-      ) AS t(canonical_govid, gov_name, govs_type, type_label, fips_state,
-             fips_county, fips_place, population_acs)
-    ) TO %s (FORMAT PARQUET)
-  ", uscogdata:::.sql_lit_chr(xwalk_path)))
-
-  cats_path <- file.path(tmp, "data", "summary_categories.parquet")
-  DBI::dbExecute(write_con, sprintf("
-    COPY (
-      SELECT * FROM (VALUES
-        ('E36', 'Test Category', 'expenditure', 'direct', NULL)
-      ) AS t(item_code, category, category_type, spend_subtype, revenue_subtype)
-    ) TO %s (FORMAT PARQUET)
-  ", uscogdata:::.sql_lit_chr(cats_path)))
-
-  # Confirm the synthetic `long` genuinely lacks harmonized_code (not just
-  # NULL values -- the column itself must be absent) before trusting the
-  # rest of this test.
-  cols <- DBI::dbGetQuery(write_con, sprintf(
-    "DESCRIBE SELECT * FROM read_parquet(%s)", uscogdata:::.sql_lit_chr(part_path)
-  ))$column_name
-  expect_false("harmonized_code" %in% cols)
-
-  url <- paste0(tmp, "/")
-
-  # (1) Full .register_views() against this v4-shaped corpus must succeed --
-  # this is the behavior the guard exists to protect.
-  con <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(con, shutdown = TRUE), add = TRUE)
-  expect_no_error(
-    uscogdata:::.register_views(con, url, manifest = list(schema_version = 4L))
-  )
-  views <- DBI::dbGetQuery(con,
-    "SELECT table_name FROM information_schema.tables
-     WHERE table_schema = 'main' AND table_type = 'VIEW'")$table_name
-  expect_true(all(c("ig_long", "ig_annotated", "spending_annotated") %in% views))
-  expect_false(any(c("ig_long_harmonized", "ig_annotated_harmonized",
-                      "spending_long_harmonized") %in% views))
-
-  # (2) Prove the gate is load-bearing: the exact SQL text of the skipped
-  # file, executed directly (bypassing .register_views()'s schema_version
-  # check) against the SAME corpus, fails because it references
-  # long.harmonized_code, a column this corpus's `long` does not have.
-  sql_dir <- system.file("sql", package = "uscogdata")
-  .read_view_sql <- function(filename) {
-    txt <- paste(readLines(file.path(sql_dir, filename), warn = FALSE), collapse = "\n")
-    gsub("\\{url\\}", url, txt, fixed = FALSE)
-  }
-  con2 <- DBI::dbConnect(duckdb::duckdb())
-  on.exit(DBI::dbDisconnect(con2, shutdown = TRUE), add = TRUE)
-  DBI::dbExecute(con2, .read_view_sql("10-long.sql"))
-  expect_error(DBI::dbExecute(con2, .read_view_sql("25-ig_long_harmonized.sql")))
-
-  # Reconciling this test with the C2 guard (expenditure-concept review):
-  # `ig_annotated`/`spending_annotated` registering cleanly above proves
-  # only that CREATE VIEW binds against a `summary_categories` with no M/L
-  # rows at all (this synthetic corpus's own summary_categories has a
-  # single E36 row, see the COPY above) -- a LEFT JOIN never fails to
-  # resolve regardless of what the joined-to table contains. It does NOT
-  # mean querying expenditure_concept = "total" against this shape is safe:
-  # exactly this corpus (schema_version reported as supported, but
-  # summary_categories predates the M/L rows cog_pipeline PR #59 added) is
-  # what .require_ig_categories() exists to catch at the *verb* level,
-  # since PR #59 shipped those rows with no schema_version bump. Confirm
-  # the new runtime guard actually fires against this same `con`.
-  expect_error(
-    uscogdata:::.require_ig_categories(con),
-    class = "uscogdata_ig_categories_unsupported"
-  )
-})
-
 test_that("spending_long filters to E/F/G/K prefixes and excludes aggregates", {
   skip_if_no_corpus()
   con <- cog_open()

vignettes/total-spending.Rmd

@@ -1,229 +0,0 @@
----
-title: "Total spending: Direct, Total, and when each is right"
-output: rmarkdown::html_vignette
-vignette: >
-  %\VignetteIndexEntry{Total spending: Direct, Total, and when each is right}
-  %\VignetteEngine{knitr::rmarkdown}
-  %\VignetteEncoding{UTF-8}
----
-
-```{r setup, include = FALSE}
-knitr::opts_chunk$set(collapse = TRUE, comment = "#>")
-```
-
-# Two questions that sound the same but aren't
-
-"Total spending" means two different things depending on whether the question
-is about one government or several:
-
-1. **"What did my county spend in total, a decade ago vs today?"** — one
-   government, tracked over time. Either `direct` or `total` spending answers
-   this correctly, as long as the same concept is used for both years.
-2. **"How do all the counties in my state compare, a decade ago vs today,
-   against the neighboring state?"** — several governments, summed together.
-   Here only `direct` gives the right answer; summing `total` across
-   governments double-counts money that passes between them.
-
-`cog_spending()`'s `expenditure_concept` argument (`"direct"` or `"total"`)
-controls which of these a query answers. This vignette walks through both
-questions with code that actually runs against the package's bundled fixture
-corpus, then explains why the second question refuses `"total"` outright.
-
-```{r}
-library(uscogdata)
-
-# Point at the bundled offline fixture (years 2011, 2012, 2019, 2020, all 50
-# states) so this vignette knits without network access. In real use,
-# USCOGDATA_URL is instead set to the published corpus URL -- see README.md.
-Sys.setenv(USCOGDATA_URL = paste0(
-  system.file("extdata/fixture_corpus", package = "uscogdata"), "/"
-))
-```
-
-The fixture doesn't carry 2017 or the present year, so the examples below use
-the closest years it does ship -- **2012 and 2020** -- in place of "2017 vs
-today" / "ten years ago vs today". Point `USCOGDATA_URL` at the published
-corpus and swap in real years; the mechanics are identical.
-
-# Archetype 1: one government's own trend
-
-For a single government, `total` is a legitimate way to describe "everything
-this government spent, including money it handed to other governments to
-spend on its behalf":
-
-```{r}
-al_total <- cog_spending(
-  "010000226085",                 # Alabama, the state government
-  years = c(2012, 2020),
-  category = "Highways",
-  expenditure_concept = "total"
-)
-al_total
-```
-
-The `intergovernmental` rows are what `"total"` adds on top of `"direct"`
-(`capital` + `operations`): Alabama's own payments out to counties and
-cities for highway work. Because this query only ever concerns Alabama,
-including that piece is safe -- there's no other government's number it
-could be double-counted against.
-
-`"direct"` (the default) answers the same trend question just as validly:
-
-```{r}
-al_direct <- cog_spending(
-  "010000226085", years = c(2012, 2020), category = "Highways"
-  # expenditure_concept = "direct" is the default; shown here for contrast
-)
-al_direct
-```
-
-Both are internally consistent series. What breaks the comparison is
-**switching concepts between the two years being compared** -- e.g. `direct`
-for 2012 and `total` for 2020 -- which manufactures a trend that isn't
-really there. Pick one concept for a given question and hold it fixed across
-every year in the series.
-
-# Archetype 2: a cross-government rollup
-
-`cog_geographic_rollup()` sums spending across state/county/city layers for
-a place. Its default -- and, as shown below, its *only* accepted value for
-`expenditure_concept` -- is `"direct"`:
-
-```{r}
-fl_rollup <- cog_geographic_rollup(
-  govids = list(
-    state  = "120000226351",                   # Florida
-    county = c("121011212191", "121099101897") # Broward + Palm Beach
-  ),
-  category = "Highways",
-  years = c(2012, 2020)
-)
-fl_rollup
-```
-
-For the neighboring state, the comparison is a single government, so it's a
-plain `cog_spending()` call rather than a rollup:
-
-```{r}
-ga_state <- cog_spending(
-  "130000226087", years = c(2012, 2020), category = "Highways" # Georgia
-)
-ga_state
-```
-
-Now the same rollup, but asking for `expenditure_concept = "total"`:
-
-```{r, error = TRUE}
-cog_geographic_rollup(
-  govids = list(state = "120000226351", county = "121011212191"),
-  category = "Highways",
-  years = 2020,
-  expenditure_concept = "total"
-)
-```
-
-`cog_geographic_rollup()` (and `cog_peer_compare()`, for the same reason)
-refuses `"total"` outright rather than silently returning an inflated
-number. The next section is why.
-
-# The mechanism
-
-Suppose Alabama gives a county $10M toward a highway project. That $10M
-shows up **twice** in the underlying corpus:
-
-- Once on Alabama's own record, coded `M44` ("to local governments,
-  Highways") -- Alabama's intergovernmental leg.
-- Again on the county's record, coded `E44` / `F44` ("Highways, current
-  operations" / "capital outlay") -- the county's direct spending, because
-  the county is the government that actually lets the contract and pays the
-  paving crew.
-
-`direct` (item codes `E`/`F`/`G`) only ever counts the second of those --
-the government that actually did the spending. `total` (Direct plus the
-`M`/`L` intergovernmental legs) counts the first one *as well*, which is
-exactly right for describing Alabama's own budget: Alabama's `total`
-genuinely includes the $10M it committed to highways, whether it built the
-road itself or paid the county to. But sum `total` across Alabama **and**
-the county, and that $10M is counted twice -- once as Alabama's payment out,
-once as the county's spending in -- reporting $20M of highway work for $10M
-actually spent.
-
-This is exactly the shape of query `cog_geographic_rollup()` exists to run
-(summing across layers of government), so it refuses `"total"` rather than
-silently overstating every multi-layer figure it produces.
-
-# How big is the risk in practice
-
-Intergovernmental transfers aren't evenly distributed by government type.
-Measured against the bundled fixture corpus (all 50 states, each of its
-four years -- 2011, 2012, 2019, 2020), intergovernmental spending as a
-share of a government's own Direct spending is:
-
-| Government type | Intergovernmental / Direct |
-|---|---|
-| State  | 16.7%-48.4% (varies by year; 24.0% pooled across all four) |
-| County | 3.4%-5.1% (varies by year) |
-| City   | 2.6%-3.1% (varies by year) |
-
-So the Direct/Total choice matters overwhelmingly for **state** governments
--- a state's Total genuinely differs from its Direct by a meaningful margin,
-while for a county or city the two are close. The state range is also far
-wider than a single flat figure would suggest: legacy wide-era years (2011:
-48.4%) carry proportionally more intergovernmental spending than the modern
-era (2019-2020: 16.7%-17.0%), so a state's Direct/Total gap can be nearly
-3x larger a decade earlier than it is today. That's also why the mistake
-this vignette warns about is easy to make unnoticed at the county/city level
-and costly at the state level: rolling up every government in a state using
-`total` instead of `direct` overstates the true figure -- measured at 7.6%
-for Alabama in FY2019, and 11.6% nationally.
-
-# Why Total = Direct + M + L, not Direct + M
-
-It's tempting to assume `total` only needs to add `M`. But `M` and `L` are
-both money the queried government itself pays **out** -- they're not two
-different accounts of a receiving government's revenue. `M` is what it
-pays to other **local** governments (e.g. a county paying a city for a
-shared paving contract); `L` is what it pays **up** to its **state**
-government (e.g. a county's contribution to a state-administered program).
-A local government's Total genuinely includes both legs, because both are
-its own spending, just routed to a different kind of recipient. On the
-bundled fixture corpus (all 50 states, 2011/2012/2019/2020), `L` is 0 for
-state governments (a state has no "payments to the state government" leg of
-its own) but is 43%-51% the size of `M` for counties (varies by year) and
-144%-189% the size of `M` for cities (varies by year; 166% pooled across
-all four) -- so a `total` that omitted `L` would silently undercount Total
-specifically for local governments, and for cities `L` is often the
-*larger* of the two legs.
-`cog_spending(expenditure_concept = "total")` includes both legs (excluding
-the `L--` family-total rollup row, which would double-count its own
-components).
-
-# Composition rules
-
-- `expenditure_concept` (whose spending counts -- Direct vs Direct plus
-  intergovernmental) is **orthogonal** to `basis` (which vintage of the
-  item-code space a query resolves against -- `"harmonized"` vs `"raw"`).
-  They combine freely: `expenditure_concept = "total", basis = "raw"` is a
-  valid, meaningful query, and so is every other pairing.
-- `expenditure_concept = "total"` is **mutually exclusive** with `recipe`: a
-  recipe already defines its own component codes (some recipes have their
-  own matching intergovernmental counterpart recipe instead -- see
-  `cog_recipes()` and the "firing suggestion" notes surfaced in
-  `cog_spending()`'s provenance), so layering a second, generic `total`
-  union on top of a recipe query has no well-defined meaning. Passing both
-  together aborts with an error naming the conflict.
-- `expenditure_concept` is a **spending-only** concept: `cog_revenue()`
-  doesn't expose it (revenue's own intergovernmental codes are a different
-  axis -- see `?cog_revenue`).
-
-# Summary
-
-- Comparing one government to itself over time: `"direct"` or `"total"`
-  both work -- pick one and hold it fixed across every year compared.
-- Comparing or summing across governments -- counties within a state, a
-  state against its neighbor, cities against counties: use `"direct"`.
-  `cog_geographic_rollup()` and `cog_peer_compare()` enforce this by
-  refusing `"total"`.
-- `"total"` = Direct (`E`/`F`/`G`) + intergovernmental (`M` to local
-  governments + `L` to the state government, excluding the `L--`
-  family-total row).