Card: drop fr tag (en-only corpus, <1% FR prose noted), add registration≠effect / absence≠inactivity limitation (commit 459a9f4)
Browse files
README.md
CHANGED
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@@ -2,7 +2,6 @@
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pretty_name: Ontario Lobbying & MPP Disclosure Graph (oico-dd structured projection)
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language:
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- en
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-
- fr
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tags:
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- government
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- lobbying
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@@ -236,41 +235,48 @@ in the OICO source, and it is scope-limited and tiered:
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topics." It is not evidence a meeting occurred, that anyone was contacted,
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or that anything was influenced. Subject matters and techniques are
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self-classified by the registrant.
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2. **
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held it and MPP Y disclosed an interest in Z" is three facts about public
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filings, not a narrative. This dataset must not be used to allege
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wrongdoing; lobbying and disclosure are the *compliance* mechanisms working
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as designed.
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-
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counts are lower bounds; de-registered filings are absent.
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-
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interest-presence prose (with limited exceptions, no dollar values). "MPP X
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holds an interest in Y" is supportable; "MPP X owns $N" is not.
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Cross-year changes reflect disclosure changes, not necessarily economic
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ones. Disclosure free text is exported verbatim (`*_text` columns);
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structured interest→organization edges were deliberately **not** extracted
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(an NLP pass with its own error rate — deferred).
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-
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the same (registration, target, subject_type) repeats across lobbying
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activities within one filing. **Always `DISTINCT` over
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`registration_no` (and `subject_type` if relevant) before counting.**
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`target_row_count` in `government_bodies` is raw-mention count, not
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registration count.
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-
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parliament granularity; by-election parliaments are multi-holder and
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tier-marked `ambiguous` (see Methodology).
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-
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filter the relevant tier columns to `confirmed` (and should state the tier
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either way). `probable` links are name-only matches.
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-
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completeness, not truthfulness.
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-
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survive as separate entities (e.g. one registration carrying both
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`Matthew Dubé` and `Matthew Dubé` as filer aliases resolved to two
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entities, ≈13 registrations affected); merging them automatically would
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violate the review discipline, so they remain split (under-merge by
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design). A handful of riding string variants likewise remain uncollapsed.
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-
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review flags, and corroboration signals are exported so a third party can
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check any call.
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@@ -306,7 +312,9 @@ graph projection): `person:slug:{member_slug}` / `person:ent:{entity_id}`,
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`riding_id`; registrations use the registry's own `registration_no`.
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Dates are ISO `YYYY-MM-DD` strings (NULL where the source omits them);
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timestamps are ISO-8601 UTC.
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lowercase/whitespace normalizations used as join keys upstream — they are not
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display names.
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@@ -380,7 +388,7 @@ Bill, Regulation, Policy/Program, …) with free-text `goal_text`. Columns:
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`subject_row_id`, `registration_no`, `subject_kind`, `subject_type`,
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`subject_text`, `subject_norm`, `goal_text`, `source`.
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-
**`registration_targets`** — ⚠ RAW-mention grain (limitation
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target mention per lobbying activity. `target_kind` ∈ `mpp` (riding-office;
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resolves to `riding_id`), `ministry`, `ministers_office`, `agency` (resolve
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to `govbody_id`), `other_institution` (kept verbatim, no resolved ref).
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@@ -460,7 +468,7 @@ source](#the-one-assertion-beyond-the-sources-minister-portfolios)):
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`match_method`, `reviewed`, `review_note`, `source`.
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**`held_by`** — one row per (riding, person, parliament) holding;
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by-election parliaments emit multiple rows marked `ambiguous` (limitation
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`term_end` NULL = ongoing. Columns: `held_by_id`, `riding_id`, `riding_raw`,
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`member_slug`, `person_id`, `parliament_number`, `term_start`, `term_end`,
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`term_start_raw`, `term_end_raw`, `ambiguous`, `confidence_tier`, `source`.
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@@ -470,7 +478,7 @@ by-election parliaments emit multiple rows marked `ambiguous` (limitation 6).
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**`disclosures`** — one row per disclosure FILING EVENT, grain
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(mpp, year, as_of_date) — an MPP can file twice in a year (by-election +
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year-end), and both rows coexist. Interest panels are verbatim free text
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-
(limitation
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`riding_raw`, `year`, `as_of`, `as_of_date`, `income_text`, `assets_text`,
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`liabilities_text`, `gifts_text`, `offices_text`, `spouse_income_text`,
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`spouse_assets_text`, `spouse_liabilities_text`, `person_resolution_tier`,
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@@ -501,11 +509,11 @@ in_term = hits[
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(hits.initial_filing_date >= hits.term_start)
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& (hits.term_end.isna() | (hits.initial_filing_date <= hits.term_end))
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]
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n = in_term.registration_no.nunique() # DISTINCT — limitation
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```
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The result is a count of *registrations declaring intent to lobby that
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office during that tenure* — a lower bound (limitation
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(limitation 1).
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## Reproducibility
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pretty_name: Ontario Lobbying & MPP Disclosure Graph (oico-dd structured projection)
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language:
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- en
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| 5 |
tags:
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- government
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- lobbying
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topics." It is not evidence a meeting occurred, that anyone was contacted,
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or that anything was influenced. Subject matters and techniques are
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self-classified by the registrant.
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+
2. **Registration ≠ effect, and absence ≠ inactivity.** A registration in this
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data records intent to lobby; it does not indicate the lobbying succeeded
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or that any outcome followed. Conversely, the absence of a registration
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does not mean no lobbying occurred — unregistered lobbying exists and is
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itself a separate compliance violation, invisible to a registry-based
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dataset. Both directions limit what can be inferred from presence or
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absence here.
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3. **Co-occurrence is not causation.** "Lobbying targeted riding X while MPP Y
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held it and MPP Y disclosed an interest in Z" is three facts about public
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filings, not a narrative. This dataset must not be used to allege
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wrongdoing; lobbying and disclosure are the *compliance* mechanisms working
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as designed.
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+
4. **Active-set lower bound.** See [Provenance](#provenance): historical
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counts are lower bounds; de-registered filings are absent.
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5. **PDS lists interests, not amounts.** MPP disclosures are
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interest-presence prose (with limited exceptions, no dollar values). "MPP X
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holds an interest in Y" is supportable; "MPP X owns $N" is not.
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| 255 |
Cross-year changes reflect disclosure changes, not necessarily economic
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ones. Disclosure free text is exported verbatim (`*_text` columns);
|
| 257 |
structured interest→organization edges were deliberately **not** extracted
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(an NLP pass with its own error rate — deferred).
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+
6. **The targets grain trap.** `registration_targets` is RAW-mention grain:
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the same (registration, target, subject_type) repeats across lobbying
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activities within one filing. **Always `DISTINCT` over
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`registration_no` (and `subject_type` if relevant) before counting.**
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`target_row_count` in `government_bodies` is raw-mention count, not
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registration count.
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+
7. **HELD_BY is parliament-level.** Term dates come from the OLA roster at
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parliament granularity; by-election parliaments are multi-holder and
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tier-marked `ambiguous` (see Methodology).
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+
8. **Name-bridge tiers are load-bearing.** Any cross-source person claim must
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filter the relevant tier columns to `confirmed` (and should state the tier
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either way). `probable` links are name-only matches.
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+
9. **Self-reported sources.** The Integrity Commissioner reviews filings for
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completeness, not truthfulness.
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+
10. **Known warts, kept honestly.** A small number of mojibake-era name twins
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survive as separate entities (e.g. one registration carrying both
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`Matthew Dubé` and `Matthew Dubé` as filer aliases resolved to two
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entities, ≈13 registrations affected); merging them automatically would
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violate the review discipline, so they remain split (under-merge by
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design). A handful of riding string variants likewise remain uncollapsed.
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+
11. **Resolution decisions are auditable, not infallible.** Match methods,
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review flags, and corroboration signals are exported so a third party can
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check any call.
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`riding_id`; registrations use the registry's own `registration_no`.
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Dates are ISO `YYYY-MM-DD` strings (NULL where the source omits them);
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timestamps are ISO-8601 UTC. Free-text fields are predominantly English; a
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small fraction of filings (<1% of rows, mostly francophone organizations'
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`goal_text` / `client_business`) contain French prose, kept verbatim. `*_norm` columns are deterministic
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lowercase/whitespace normalizations used as join keys upstream — they are not
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display names.
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`subject_row_id`, `registration_no`, `subject_kind`, `subject_type`,
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`subject_text`, `subject_norm`, `goal_text`, `source`.
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+
**`registration_targets`** — ⚠ RAW-mention grain (limitation 6): one row per
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target mention per lobbying activity. `target_kind` ∈ `mpp` (riding-office;
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resolves to `riding_id`), `ministry`, `ministers_office`, `agency` (resolve
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to `govbody_id`), `other_institution` (kept verbatim, no resolved ref).
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`match_method`, `reviewed`, `review_note`, `source`.
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**`held_by`** — one row per (riding, person, parliament) holding;
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by-election parliaments emit multiple rows marked `ambiguous` (limitation 7).
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`term_end` NULL = ongoing. Columns: `held_by_id`, `riding_id`, `riding_raw`,
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`member_slug`, `person_id`, `parliament_number`, `term_start`, `term_end`,
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`term_start_raw`, `term_end_raw`, `ambiguous`, `confidence_tier`, `source`.
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**`disclosures`** — one row per disclosure FILING EVENT, grain
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(mpp, year, as_of_date) — an MPP can file twice in a year (by-election +
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year-end), and both rows coexist. Interest panels are verbatim free text
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(limitation 5). Columns: `disclosure_id`, `person_id`, `mpp_id`, `mpp_name`,
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`riding_raw`, `year`, `as_of`, `as_of_date`, `income_text`, `assets_text`,
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`liabilities_text`, `gifts_text`, `offices_text`, `spouse_income_text`,
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`spouse_assets_text`, `spouse_liabilities_text`, `person_resolution_tier`,
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(hits.initial_filing_date >= hits.term_start)
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& (hits.term_end.isna() | (hits.initial_filing_date <= hits.term_end))
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]
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n = in_term.registration_no.nunique() # DISTINCT — limitation 6
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```
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The result is a count of *registrations declaring intent to lobby that
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office during that tenure* — a lower bound (limitation 4), not a contact log
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(limitation 1).
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## Reproducibility
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