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).

R/manifest.R

@@ -128,7 +128,17 @@
 }
 
 #' @noRd
-.validate_schema <- function(manifest, supported = c(4L, 5L)) {
+#' Schema v6 (FIPS geography harmonization, 2026-07-22) is accepted alongside
+#' 4/5. v6 renamed the long table's fips_state_code/fips_county_code to
+#' fips_state_asof/fips_county_asof and added cog_legacy_state/
+#' cog_legacy_county (26 -> 28 cols); this package references NONE of those
+#' columns, so no code change was needed. NOTE the SILENT semantic change for
+#' any consumer of the raw long table: long fips_state/fips_county are now
+#' PRESENT/harmonized geography (current county identity carried back to every
+#' year, matching canonical_fips_xwalk) rather than as-of-year; as-of-year
+#' moved to the *_asof columns. This package's own geography always came from
+#' the xwalk (already present-based), so behaviour is unchanged.
+.validate_schema <- function(manifest, supported = c(4L, 5L, 6L)) {
   if (!manifest$schema_version %in% supported) {
     cli::cli_abort(c(
       "Corpus schema version mismatch.",

R/session.R

@@ -12,7 +12,7 @@ cog_open <- function(url = .resolve_url(),
   DBI::dbExecute(con, "INSTALL httpfs; LOAD httpfs;")
 
   manifest <- .fetch_or_cache_manifest(url, cache_dir)
-  .validate_schema(manifest, supported = c(4L, 5L))
+  .validate_schema(manifest, supported = c(4L, 5L, 6L))
   .validate_scope(manifest)
 
   .register_views(con, url, manifest)

R/spending.R

@@ -141,7 +141,7 @@ cog_spending <- function(govid, years, category = NULL,
     harmonization <- .build_harmonization_block(
       con, govid, years, resolved, flow_prefixes
     )
-    suggestions <- .build_suggestions(con, govid, years, category, result, resolved$basis)
+    suggestions <- .build_suggestions(con, govid, years, category, resolved$basis)
   }
 
   prov <- .build_provenance(

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
@@ -12,53 +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.
+# 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$suggestions` list for a (non-recipe) basis = "harmonized"
-#' verb call: recipes whose generic join would fill a real gap in `result`.
-#'
-#' @param con Active DuckDB connection.
-#' @param govid Character vector of canonical_govid values (the verb's raw
-#'   `govid`).
-#' @param years Integer vector of requested years.
-#' @param category `category` argument as passed to the verb (character
-#'   vector or `NULL`; suggestions are only computed when non-NULL).
-#' @param result The verb's already-computed result tibble (post basis
-#'   query, pre per_capita/adjust_to_year).
-#' @param basis The *resolved* basis (`"harmonized"` or `"raw"`).
-#' @return List of `list(recipe_id, label, available_years, hint)`, possibly
-#'   empty.
+#' Recipe components that are classified under the requested category --
+#' the codes a category-scoped query actually "requests". A recipe can
+#' have components outside the category (e.g. general_gov_e89_wide's E85
+#' leg has no category assignment); those never trigger on their own, they
+#' just were never part of what this query asked for.
 #' @noRd
-.build_suggestions <- function(con, govid, years, category, result, basis) {
-  if (!identical(basis, "harmonized") || is.null(category)) return(list())
-
-  candidates <- DBI::dbGetQuery(con, sprintf(
-    "SELECT DISTINCT recipe_id FROM harmonization_recipes
-     WHERE component_code IN (
-       SELECT DISTINCT item_code FROM summary_categories WHERE category IN (%s)
-     )",
+.category_recipe_components <- function(con, category) {
+  DBI::dbGetQuery(con, sprintf(
+    "SELECT DISTINCT r.recipe_id, r.component_code, r.year_min, r.year_max,
+            r.gov_type_scope
+     FROM harmonization_recipes r
+     JOIN summary_categories sc
+       ON sc.item_code = r.component_code AND sc.category IN (%s)",
     .sql_lit_chr(category)
-  ))$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
@@ -66,13 +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
@@ -83,13 +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,

README.md

@@ -25,6 +25,22 @@ package implements.
 - `USCOGDATA_CACHE_DIR` — optional override for the manifest cache directory
 - `USCOGDATA_MANIFEST_TTL_SECS` — optional manifest re-fetch TTL (default 3600)
 
+## Raw-parquet caveat: `survey_weight` is not an aggregation weight
+
+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

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

@@ -1,11 +1,24 @@
 {
-  "schema_version": 5,
-  "built_at": "2026-07-19T03:08:41Z",
-  "pipeline_commit": "ece9b32",
+  "schema_version": 6,
+  "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": {
-    "census_source_downloaded": "unknown",
-    "cpi_vintage": "FRED CPIAUCSL",
+    "source_vintages": {
+      "2012": "10162019",
+      "2013": "10162019",
+      "2014": "10162019",
+      "2015": "10162019",
+      "2016": "10162019",
+      "2017": "06102021",
+      "2018": "06102021",
+      "2019": "06102021",
+      "2020": "06122023",
+      "2021": "06122023",
+      "2022": "06052025",
+      "2023": "06052025"
+    },
+    "registry_rows": 148,
     "acs_vintage": "ACS 2018-2022 5-year"
   },
   "scope": {
@@ -14,8 +27,8 @@
     "scope_note": "v0.1 covers state, county, city/municipality, and township governments. Special districts (type 4) and school districts (type 5) are excluded pending validation in a future cycle."
   },
   "schema": {
-    "long_column_count": 26,
-    "long_columns": ["fips_state", "type", "fips_county", "govid", "gov_blank", "gov_name", "county_name", "fips_state_code", "fips_county_code", "fips_place_code", "population", "popyear", "enrollment", "enrollyear", "function_code", "sch_level_code", "fiscal_year_end", "srvy_year", "item_code", "amt", "srv_data", "impute_flag", "is_aggregate", "canonical_govid", "harmonized_code", "survey_weight"],
+    "long_column_count": 28,
+    "long_columns": ["fips_state", "type", "fips_county", "govid", "gov_blank", "gov_name", "county_name", "fips_state_asof", "fips_county_asof", "cog_legacy_state", "cog_legacy_county", "fips_place_code", "population", "popyear", "enrollment", "enrollyear", "function_code", "sch_level_code", "fiscal_year_end", "srvy_year", "item_code", "amt", "srv_data", "impute_flag", "is_aggregate", "canonical_govid", "harmonized_code", "survey_weight"],
     "data_dictionary": "docs/data_dictionary.md"
   },
   "files": {
@@ -23,41 +36,41 @@
       {
         "year": 2011,
         "path": "data/long/year=2011/part-0.parquet",
-        "sha256": "76c2153ef0a94c3551a24751aa08225fc937fafb579f10fd0750848d781dc471",
-        "row_count": 3037606,
-        "size_bytes": 4985667
+        "sha256": "84302ab364dc9fc3b3fbbc3c3f8b826e3508b4d73ff7c42d094d3863cd1e37b5",
+        "row_count": 2864212,
+        "size_bytes": 3845911
       },
       {
         "year": 2012,
         "path": "data/long/year=2012/part-0.parquet",
-        "sha256": "a9bb10d04887490376a4b030a03a4ca1e0f1f9fbca5f7d99ea7ca7434c42b2bc",
+        "sha256": "b82ac82d5e35f844b26c887445601f3748438c52c998ba4e403b025941a6f170",
         "row_count": 1163338,
-        "size_bytes": 5900191
+        "size_bytes": 5929917
       },
       {
         "year": 2019,
         "path": "data/long/year=2019/part-0.parquet",
-        "sha256": "475481fcfbb030f96cae457cbda824512a2da6f97f4c6d12a75130979e4331f9",
+        "sha256": "5cbd4726dcc7d0dab5c2a05a64702e979533ae119ed0587073cd31c089e0d737",
         "row_count": 318139,
-        "size_bytes": 1717345
+        "size_bytes": 1719548
       },
       {
         "year": 2020,
         "path": "data/long/year=2020/part-0.parquet",
-        "sha256": "7cdf3eb1a73c34e6a3d22befdf7ccdd0b44b1e6b1cf4491159a38a5a24a1b005",
+        "sha256": "ee548fec80bf1beda844fe03916ac145f10dd34c45968407cc330ec260935f00",
         "row_count": 317500,
-        "size_bytes": 1720794
+        "size_bytes": 1722918
       }
     ],
     "metadata": [
       {
         "path": "data/canonical_alias.parquet",
-        "sha256": "fa27ce4b59e286ace05fbcb9f59a910b8e483fd6c58ddf01875a210b966809cb",
+        "sha256": "3f617051c23a99bea322889857f7106df0c92954564afeec181df7083ee6698e",
         "description": "canonical_alias.parquet"
       },
       {
         "path": "data/canonical_fips_xwalk.parquet",
-        "sha256": "b6e2c4cb748141f6f2e324d6704c13830d2a68ad57bbb73d04ac54b881d1285b",
+        "sha256": "f98742f941269dacf8f7de5c273aa4dd4e75017a5bb70c054da35852a95a8d46",
         "description": "canonical_fips_xwalk.parquet"
       },
       {
@@ -67,7 +80,7 @@
       },
       {
         "path": "data/harmonization_map.parquet",
-        "sha256": "52b4f3f94e65231aa869445946df7a0cfebf8fef1940f800e08287b53d09ab42",
+        "sha256": "4cf32d0f817079ba4f28dc0ce65450d3247ebbf08d94c0c26c0d02af597bf812",
         "description": "harmonization_map.parquet"
       },
       {
@@ -77,7 +90,7 @@
       },
       {
         "path": "data/series_breaks.parquet",
-        "sha256": "049bd7365dae14e357f6e57765dc5a069440bab46facce237d7ba2ec94b0b113",
+        "sha256": "b0b6794b6887a4f300079adfa10029c2a77109faa4952fbff1c5a270793cc02b",
         "description": "series_breaks.parquet"
       }
     ]

tests/testthat/test-manifest.R

@@ -111,15 +111,20 @@ test_that("cog_manifest returns the active session's parsed manifest", {
   })
 })
 
-test_that(".validate_schema accepts schema_version 4 and 5, rejects others", {
+test_that(".validate_schema accepts schema_version 4, 5 and 6, rejects others", {
   expect_silent(uscogdata:::.validate_schema(list(schema_version = 4L)))
   expect_silent(uscogdata:::.validate_schema(list(schema_version = 5L)))
+  # v6 = FIPS geography harmonization (2026-07-22): _code -> _asof rename +
+  # cog_legacy_* columns (26 -> 28 cols). This package references none of the
+  # renamed columns and its geography comes from the xwalk, so v6 is accepted
+  # without behavioural change -- see .validate_schema()'s note.
+  expect_silent(uscogdata:::.validate_schema(list(schema_version = 6L)))
   expect_error(
     uscogdata:::.validate_schema(list(schema_version = 3L)),
     "schema_version"
   )
   expect_error(
-    uscogdata:::.validate_schema(list(schema_version = 6L)),
+    uscogdata:::.validate_schema(list(schema_version = 7L)),
     "schema_version"
   )
 })

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-spending.R

@@ -250,12 +250,17 @@ test_that("provenance carries basis + harmonization block with na_rows_excluded"
     expect_true(prov$harmonization$applied)
     expect_true(prov$harmonization$na_rows_excluded >= 0L)
     expect_true(prov$harmonization$na_amount_excluded >= 0)
-    # Data-verified for this fixture: none of the discontinued_na rulings
-    # (S74, Z61, X04, X06, the debt-detail family, L24) fall inside the
-    # E/F/G/K spending prefixes, so the exclusion count is exactly zero for
-    # every year in the bundled window -- see
-    # docs/phase_r_harmonization_review.md § 1.3/1.4.
-    expect_equal(prov$harmonization$na_rows_excluded, 0L)
+    # Data-verified for the v6 fixture (corpus 2026-07-22). The Task 18 map
+    # extension added E/F/G-prefix discontinued_na rulings the earlier pin's
+    # comment predated: E21/F21/G21 (Education NEC local, SB184-186,
+    # "trivial; explicit-NA, full wide-era window"). Broward's 2011 legacy
+    # partition zero-pads exactly those three codes, so this query now
+    # excludes 3 NA-harmonized rows -- all with amt = 0, hence the excluded
+    # AMOUNT stays exactly zero. (The other discontinued_na rulings -- S74,
+    # Z61, X04, X06, the debt-detail family, L24 -- remain outside the
+    # E/F/G/K prefixes.) See docs/phase_r_harmonization_review.md § 1.3/1.4
+    # and cog_pipeline data/harmonization_map.csv E21/F21/G21 rows.
+    expect_equal(prov$harmonization$na_rows_excluded, 3L)
     expect_equal(prov$harmonization$na_amount_excluded, 0)
   })
 })