diff --git a/data-raw/measure_signposting_rate.R b/data-raw/measure_signposting_rate.R
index 00492f7..34651e1 100644
--- a/data-raw/measure_signposting_rate.R
+++ b/data-raw/measure_signposting_rate.R
@@ -24,9 +24,41 @@
 #     sibling component to supply the covering evidence -- the shipped,
 #     corrected implementation.
 #
-# This script MEASURES the deltas; it does not decide whether the added
-# signposting "noise" going coarse -> percode is acceptable. That is
-# Jared's ruling at Checkpoint R3 (see
+# 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
@@ -145,9 +177,27 @@
   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) {
@@ -172,21 +222,140 @@
   )
   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),
-    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,
+    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$additions, max_rows))
+}
+
 #' Measure the coarse-vs-per-code signposting suggestion rate over a
 #' realistic query battery (every category x a pre/post-boundary_year span
 #' x up to n_gov sampled governments).
@@ -290,6 +459,14 @@ measure_signposting_rate <- function(corpus_url = Sys.getenv("USCOGDATA_URL", un
   stopifnot(all(detail$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(),
@@ -299,6 +476,9 @@ measure_signposting_rate <- function(corpus_url = Sys.getenv("USCOGDATA_URL", un
     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))
@@ -336,19 +516,27 @@ measure_signposting_rate <- function(corpus_url = Sys.getenv("USCOGDATA_URL", un
       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
+    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
   ))
 }
 
@@ -365,5 +553,11 @@ if (identical(environment(), globalenv()) && sys.nframe() == 0L) {
   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")
 }
diff --git a/tests/testthat/test-signposting-harness.R b/tests/testthat/test-signposting-harness.R
new file mode 100644
index 0000000..4872b79
--- /dev/null
+++ b/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")
+})