.build_suggestions()'s recipe-candidate sub-select was keyed on `WHERE category IN (<category>)`. The reserved pseudo-category "All Categories" is never itself a row in summary_categories.category, so in all-categories mode `candidates` always came back empty and coverage signposting (uscogdata#9) was structurally impossible for the one mode whose entire premise is "you cannot sum the wrong scope" -- measured on Los Angeles County FY2011: category = "Public Welfare" reports 2 suggestions (incl. $271,589,000 excluded E68), category = "All Categories" reported 0, silently losing that same signal. Apply the branch's own design principle: the concept boundary is subtype, not category. .build_suggestions() now accepts all_categories/subtype_col/ subtype_scope (all optional, default off, so no other caller's behaviour changes) and, when all-categories mode is active, scopes the candidate sub-select by `<subtype_col> IN (<subtype_scope>)` instead -- symmetric with .build_verb_sql()'s own WHERE predicate. The M/L recipe exclusion and the is.null(category) early return are unchanged. After the fix, LA County FY2011 "All Categories" reports 5 suggestions, including welfare_cash_e68_wide for the exact $271,589,000 gap. Adds two covering tests to test-all-categories.R using the bundled fixture (AL state gov, FY2011, "Corrections"): one end-to-end (per-category and all-categories both signpost the same recipe) and one direct on .build_suggestions() proving the subtype-vs-category branch is what changes the query. Updates the 0.2.0 NEWS entry.
301 lines
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Markdown
301 lines
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Markdown
# uscogdata 0.2.0
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## New features
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* `cog_spending()` and `cog_revenue()` accept the reserved category
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`"All Categories"`, returning one summed row per
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`(year, canonical_govid, subtype)` across every category inside the
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requested concept's subtype scope. Filtering the result to
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`spend_subtype == "operations"` gives an operating-expenditure total.
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`cog_geographic_rollup()` inherits it,
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which is the efficient way to build a geographic total — previously a
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caller had to issue one rollup per category and sum the results
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(cog-api#37).
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`"All Categories"` is not the same thing as `expenditure_concept = "total"`.
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The concept chooses which subtypes are in scope; `"All Categories"` chooses
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whether the rows inside that scope are broken out or summed.
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* `cog_categories()` advertises `"All Categories"` for the expenditure and
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revenue vocabularies, so the reserved value is discoverable.
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* Coverage signposting (see "Signposting now catches partially-suppressed
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categories" below) now also works in `category = "All Categories"` mode.
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The recipe-suggestion candidate query used to be scoped by `category`,
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which is never a match for the reserved `"All Categories"` value, so
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`provenance$suggestions` always came back empty there — the one mode whose
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whole point is "you cannot sum the wrong scope" was silently unable to
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signal a wrong scope. The candidate query is now scoped by the concept's
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subtype allowlist instead, symmetric with how `.build_verb_sql()` itself
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scopes the summed total: Los Angeles County FY2011, `category = "All
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Categories"` still excludes $271,589,000 of aggregate-published Public
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Welfare (`E68`), but now names `recipe = "welfare_cash_e68_wide"` to
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recover it instead of reporting zero suggestions.
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## Documentation
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* `cog_geographic_rollup()` and `cog_peer_compare()` now document that
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`provenance$coverage`'s `n_units_reporting` is **category-conditional** and
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is not a response rate: a government that was surveyed and genuinely spends
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nothing in the requested category is indistinguishable from one never
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surveyed (uscogdata#36).
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# uscogdata 0.1.0 (development)
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## Signposting now catches partially-suppressed categories
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* A coverage suggestion used to fire only when a category returned **no rows
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at all** in a requested year. That missed the more dangerous case: a
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category that still returns rows while silently dropping component codes
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the wide era publishes only as aggregates (#9). `cog_spending(category =
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"Public Welfare")` for FY2011 returned a plausible figure that omitted
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`E67`/`E68` entirely -- for Los Angeles County, $2,075,461,000 of a true
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$5,261,404,000, a 39% understatement, with `provenance$suggestions` empty.
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* Suggestions now also fire on **partial** coverage, and every suggestion
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carries `trigger` (`"empty_year"` or `"suppressed_component"`),
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`suppressed_amount`, `suppressed_years` and `suppressed_codes`, so a caller
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can see how much is missing and decide whether to re-run with the recipe.
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* `cog_revenue()` gets the same fix through the shared verb path. Alaska's
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FY2011 `Miscellaneous Revenue` reported $943,842,000 while dropping
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$1,899,995,000 of aggregate-published `U4-` rents and royalties.
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* The trigger stays recipe-driven, so it only fires where a harmonization
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recipe actually exists to name the fix. `higher_ed_e18_wide` and
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`general_gov_e89_wide` stay silent in every year measured on the bundled
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fixture, because their components are ordinary classified leaves even
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pre-2012.
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* The `suppressed_component` trigger (and any `suppressed_amount`/
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`suppressed_codes` an `empty_year` fire also carries) is scoped to the
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calling verb's own flow family: `cog_spending()` only ever measures E/F/G
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component dollars, `cog_revenue()` only T/A/U/B/C/D. A component from the
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OTHER flow family reports `suppressed_amount = 0` rather than a fabricated
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claim. The `empty_year` trigger itself is not flow-scoped -- a category
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belonging to the other flow (e.g. `cog_spending(category = "IG Local")`)
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still returns zero rows and can still fire, in any year including modern
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ones, naming the recipe whose own generic join finds real data for this
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government. That is a mis-scoped query, not a corpus-format gap, so its
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`suppressed_amount` is correctly 0.
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## New: `cog_balances()` for cash-and-security holdings
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* New `cog_balances()` exposes the 14 cash-and-security holding codes
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(`category_type = "balance"`): fund balances, retirement system holdings and
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insurance trust balances (#25). Holdings are a stock, not a flow, so the verb
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has no `expenditure_concept` / `revenue_concept` / `complete` arguments, and
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no `subtype` argument either -- for holdings, `category` is a strict
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coarsening of `balance_subtype`, so `category = "Fund Balances"` is exactly
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the `general` family (`W01`/`W31`/`W61`).
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* `cog_balances()` results carry `provenance$balance_caveats`, recording that
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Census holdings are gross rather than GAAP fund balance, and the measured
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coverage window of each subtype family.
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## Multi-government aggregates now disclose their reporting coverage
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* The Census of Governments is a **complete census only in years ending in 2
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and 7**; every other year is a sample, and the sample varies enormously. On
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the bundled fixture, Wisconsin's 608-city universe rolls up **597**
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governments in FY2012 and **112** in FY2019 — an 18%-to-98% swing the
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return value said nothing about, so a statewide total resting on a fifth of
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the universe looked exactly like one resting on all of it.
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* `cog_geographic_rollup()`, `cog_peer_compare()` and `cog_find_peers()` gain
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`coverage`:
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| value | effect |
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|---|---|
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| `"all"` (default) | every unit that reported that year — unchanged behaviour |
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| `"census"` | census years only; aborts if the range holds none rather than returning nothing |
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| `"consistent"` | only units reporting in *every* requested year — a balanced panel |
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* **Regardless of mode**, every result now carries `provenance$coverage` with
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per-year `n_units_reporting`, `n_units_expected` and `is_census_year`, plus
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`provenance$coverage_mode`. `cog_explain()` prints a "Reporting coverage"
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section. So the default mode can no longer mislead silently.
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* `is_census_year` is a statement about the **survey calendar**, never a claim
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of completeness: FY1967 is a census year in which only 97 of Wisconsin's 608
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cities report. `n_units_reporting` is the number that tells the truth.
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* On `cog_peer_compare()` the target is exempt from `"consistent"` balancing —
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it is the subject of the comparison, not a member of the cohort — and the
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`summary_*` quantiles are computed after the filter, so they describe the
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cohort actually returned. `n_units_reporting` counts peers only, against the
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cohort size.
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* On `cog_find_peers()`, `coverage` governs the cohort **vintage** when `year`
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is `NULL`: `"census"` snaps to the most recent census year with an observed
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population, so a cohort is not built from a sample year in which most of the
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candidate universe is absent.
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## `complete = TRUE`: absent cells, labelled with why they are absent
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* `cog_spending()` and `cog_revenue()` gain `complete`, defaulting to `FALSE`
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(today's behaviour). With `complete = TRUE` the requested grid is filled
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from the corpus's `code_set` table and every row carries a new
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`value_source` column:
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| `value_source` | meaning | `amt_nominal` |
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| `reported` | the corpus carries this cell | as published |
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| `census_zero` | dense-source year (≤ FY2011), cell absent — Census published `$0` | `0` |
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| `not_reported` | sparse-source year (≥ FY2012), cell absent — unknown | `NA` |
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The `NA` is deliberate and is the whole point: filling a modern absence
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with `0` would invent data, which is precisely the error the corpus's
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representation contract exists to prevent.
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* This restores information the reader lost when the corpus was sparsified
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(`SB194`, cog_pipeline#64) — a wide-era query whose cells were all `$0`
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had begun returning nothing at all — and improves on what came before it,
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since the pre-sparsification corpus could not distinguish a published zero
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from an unreported cell either.
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* The grid is scoped to each government's **own type**, so a county is never
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filled with cells only a state can report.
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* Needs a corpus published from 2026-07-29 onward (when `representation` and
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`code_set` began shipping); aborts with class
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`uscogdata_representation_unavailable` otherwise. Gated on the manifest
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listing those tables rather than on `schema_version`, which was never
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bumped for the change. Not available with `recipe` or
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`expenditure_concept = "total"` — neither draws its cells from `code_set`.
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* `provenance$completion` reports `applied`, `rows_filled`, and the per-year
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`absence_means` rule; `cog_explain()` prints a "Completion" section.
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## Corpus-wide series breaks now reach users (`corpus_break_refs`)
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* Four catalogued series breaks carry `fin_code = "ALL"` — caveats about the
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corpus as a whole rather than about one item code. `series_break_refs` is
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built by matching `fin_code` against the item codes in the result, and no
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row's `item_code` is ever the literal `"ALL"`, so **none of them could ever
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be surfaced**: `SB085` (dollar precision across the 1976/1977 boundary),
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`SB087` (imputation exclusion from FY2002), `SB194` (the dense → sparse
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representation change at FY2012) and `SB086` (the government id scheme
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change at FY2017).
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* Provenance gains `corpus_break_refs`, selected on the break-year window
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alone and disjoint from `series_break_refs` by construction, so a consumer
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can tell a whole-result caveat from a break in one series. `cog_explain()`
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prints them under their own "Corpus-wide caveats" heading. cog-api passes
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provenance through verbatim, so the field appears there without an API
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change.
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* `SB194` is the one that made this urgent: a query spanning FY2011 → FY2012
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crosses the boundary where an absent cell stops meaning "Census published
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`$0`" and starts meaning "not reported", and until now nothing said so.
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## Bundled fixture regenerated against the sparsified corpus
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* `inst/extdata/fixture_corpus/` now tracks the corpus published on
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2026-07-29 (`pipeline_commit 83f9715`, schema v6). The wide era no longer
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stores explicit zeros: FY2011 fell from 2,864,212 rows to 496,004, of
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which none are `$0`. **Absence now means two different things** — in a
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`dense_source` year (≤ FY2011) an absent cell means Census published `$0`;
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in a `sparse_source` year (≥ FY2012) it means not reported. The corpus
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carries that rule in two new tables the fixture now ships,
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`representation.parquet` and `code_set.parquet`, alongside
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`census_collection_coverage.parquet` and `lineage_events.parquet`
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(all ten publish-tree metadata tables, up from six). Catalogued upstream
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as series break `SB194`.
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* `cog_categories()` gains an `assistance` spending subtype: the J-prefix
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aid/benefit codes (`J19`, `J67`, `J68`, `J85`) are categorised now that
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the upstream crosswalk covers every flow code carrying dollars.
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* Two consequences worth knowing about, both visible in provenance rather
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than in returned dollars. The harmonization block's `na_rows_excluded`
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counts only rows that exist, so wide-era codes that were zero-padded no
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longer appear there. Coverage-gap `suggestions` are presence-based for the
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same reason, so a recipe whose component codes were all `$0` for a given
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government-year is no longer suggested for it.
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* `tests/testthat/test-fixture-vintage.R` pins these structural facts, so a
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fixture left behind by a future publish fails loudly instead of letting the
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suite pass against a corpus that no longer exists.
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## Breaking: corpus schema_version 4 (Phase P canonical ids)
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* The package now requires corpus `schema_version = 4` (`MinCorpusSchema` /
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`MaxCorpusSchema` in `DESCRIPTION` are both `4`); older corpora built
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against schema 3 are rejected by `cog_open()` with a clear version-mismatch
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error. `canonical_govid` is now uniformly 12 characters across every
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vintage the corpus covers (previously a mix of 9-char legacy ids and
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12-char FIPS ids depending on source year) — **every hardcoded
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`canonical_govid` literal from a pre-Phase-P corpus is now invalid** and
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must be re-resolved via `cog_gov_search()` or the new `canonical_alias`
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lookup table. `canonical_fips_xwalk` gains four columns
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(`legacy_govs_id`, `census_geoid`, `id_source`; `confidence` is renamed to
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`pop_confidence`) and a companion `canonical_alias` table ships in the
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corpus for mapping legacy/alternate ids onto the current canonical
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namespace. The bundled fixture corpus (`inst/extdata/fixture_corpus/`) has
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been regenerated against the Phase P publish tree, now ships the full
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`canonical_fips_xwalk` and `canonical_alias` master tables alongside the
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2019-2020 long partitions, and is reproducible via
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`data-raw/regenerate_fixture_corpus.R`.
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## Clearer errors when `USCOGDATA_URL` is unconfigured or returns non-JSON
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* `cog_open()` now aborts with the `uscogdata_url_not_configured` error
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class when the resolved corpus URL still contains the placeholder
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`REPLACE_WITH_SHARE_TOKEN` sentinel (or is empty). The message lists both
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remediation paths (`Sys.setenv(USCOGDATA_URL = ...)` and
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`options(uscogdata.url = ...)`) and points at the bundled fixture for
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offline testing. Previously the package proceeded to fetch the placeholder
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URL, cached the resulting HTML welcome page, and failed downstream with a
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cryptic `jsonlite` lexical-error.
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* `.fetch_or_cache_manifest()` now parses the HTTP response body before
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persisting it. Non-JSON responses (login pages, 404 HTML) raise
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`uscogdata_invalid_manifest` with the URL, Content-Type, and underlying
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parse error — and never write to the on-disk cache.
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* Manifest cache writes are now atomic (write to `manifest.json.tmp.<pid>`
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in `cache_dir`, then `file.rename` over the target), so an interrupted
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fetch cannot replace a previously-good cache.
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* Existing caches with non-JSON content (poisoned by the prior code path)
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are silently refetched instead of returning a parse error to the caller.
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* Local `USCOGDATA_URL` paths whose `manifest.json` is not valid JSON now
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surface the same `uscogdata_invalid_manifest` class with file context.
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## Per-capita denominators now use per-year Census F-33 population
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* `cog_spending()` and `cog_revenue()` previously divided all years' amounts
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by a single ACS 2018-2022 estimate (`canonical_fips_xwalk.population_acs`),
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producing biased per-capita values for time-series analysis. They now
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divide by the F-33 `population` recorded on each gov-year via the new
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`gov_population_yearly` view. Result tibbles gain a `pop_source` column
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with values `"census_f33"` or `"unavailable"`. `notes` is updated to
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concatenate multiple notes with `"; "`.
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## Peer cohorts can be set to a chosen year
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* `cog_find_peers()` adds a `year` argument (default: most recent year for
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which the target has an observed population in `gov_population_yearly`).
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The returned column previously named `population_acs` is now `population`
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and reflects the cohort year's vintage. The cohort year is attached to the
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returned tibble as `attr(x, "cohort_year")`.
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* `cog_peer_compare()` now stamps a `cohort_year` column on its result (read
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from the peers tibble's attribute) and records `cohort_year` plus
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`cohort_govids` in provenance. When the caller supplies a bare character
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vector instead of a `cog_find_peers()` result, `cohort_year` is `NA`.
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## Rollups exclude govs missing population
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* `cog_geographic_rollup(per_capita = TRUE)` drops rows whose government has
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`pop_source == "unavailable"` and records the dropped govids in
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`provenance$rollup$excluded_govids`. This excludes special districts
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(type 4) and school districts (type 5) from per-capita rollups by design.
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## New: vignette and provenance metadata
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* New vignette `population-denominators` covers the four population sources,
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the type-4/5 coverage gap, the popyear quirk, and how to build moving-window
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peer cohorts manually.
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* Provenance gains `transformations$per_capita$popyear_range` and
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`pop_source_counts`. `cog_explain()` renders both.
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## New features
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* `cog_gov_search()` gains a **basket mode**: passing vector `name`
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/ `state` / `type` arguments resolves multiple place names in one
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call and returns a tibble of canonical rows in input order, ready
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to pipe into `cog_spending()` / `cog_revenue()`. Per-row resolution
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follows an exact-then-substring matching algorithm with deterministic
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disambiguation; ambiguous and missing entries are surfaced via a
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sidecar audit tibble plus a single console summary message.
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* New exports `cog_basket_resolution()` and `cog_basket_unresolved()`
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expose the basket sidecar for iterative query refinement.
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## Breaking changes
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* The first formal of `cog_gov_search()` was renamed from `pattern`
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to `name`. All existing call sites in `cog_explorer/` and the
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package itself use positional first-arg, so this rename is
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non-breaking in practice. Callers that pass `pattern = ...` by name
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must update to `name = ...`.
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