fec_contributions

Data license: Public Domain (U.S. Government data) · Data source: Federal Register API & Regulations.gov API

4,489,134 rows sorted by transaction_dt descending

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CREATE TABLE fec_contributions (
    cmte_id TEXT,
    cmte_name TEXT,
    cand_id TEXT,
    cand_name TEXT,
    transaction_dt TEXT,
    transaction_amt REAL,
    entity_tp TEXT,
    state TEXT,
    -- employer / occupation DROPPED (Tony 2026-07-13): donor-level fields, 147/131 nameless rows of
    -- 4.4M, zero analytic value — removed so "DataDawn publishes no donor-level records" is categorical.
    -- ⚠️ RULE — NEVER SUM(transaction_amt) over fec_contributions without filtering transaction_tp.
    -- (findings_register Pattern 4 / audit_charter §I.4 — summed-money flow-label verification.)
    -- FEC itpas2 type code: 24K/24Z = contributions RECEIVED by the candidate (~21% of $, the real
    -- "received" money); 24A = independent expenditure spent AGAINST (~51%); 24E = IE spent FOR (~25%);
    -- 24C/24F/24N = coordinated/communication cost. Summing all types is the 2026-05-25
    -- fec_total_received bug: ~79% outside spending mislabeled "received," most of it attack ads.
    -- Filter to ('24K','24Z') for received; surface 24A/24E separately + clearly labeled
    -- (fec_ie_against / fec_ie_for). The org/company/docket hubs aggregate this table the same way —
    -- apply the filter there too. See bestpractices/member_hub_data_audit_2026-05-25.md.
    transaction_tp TEXT,
    cycle INTEGER NOT NULL
);
CREATE INDEX idx_fec_contrib_cand ON fec_contributions(cand_id);
CREATE INDEX idx_fec_contrib_cmte ON fec_contributions(cmte_id);
CREATE INDEX idx_fec_contrib_cycle ON fec_contributions(cycle);
CREATE INDEX idx_fec_contrib_amt ON fec_contributions(transaction_amt);
CREATE INDEX idx_fec_contrib_cand_tp ON fec_contributions(cand_id, transaction_tp);