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"muni_id", "body_name", "role", "first_seen_vote", "last_seen_vote", "n_votes", "n_meetings", "aliases", "sources", "confidence", "match_method", "updated_at"], "primary_keys": [], "count": 20469, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "people_aliases", "columns": ["muni_id", "raw_name", "person_id", "n_votes", "updated_at"], "primary_keys": [], "count": 21636, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "people_cf_bridge", "columns": ["person_id", "cf_source", "cf_filer_key", "cf_filer_name", "cf_filer_id", "muni_id", "office", "n_txns", "match_method", "confidence", "evidence", "updated_at"], "primary_keys": [], "count": 283, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "people_cf_candidates", "columns": ["cf_source", "cf_filer_key", "cf_filer_name", "muni_id", "office", "n_txns", "person_id", "candidate_person_ids", "reason", "status", "evidence", "updated_at"], "primary_keys": [], "count": 17, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "person_vote_stats", "columns": ["person_id", "muni_id", "canonical_name", "n_votes", "n_yea", "n_nay", "n_abstain", "n_present", "n_absent", "n_other", "n_meetings", "n_decided", "n_contested", "n_dissents", "dissent_rate", "attendance_rate", "first_seen_vote", "last_seen_vote", "updated_at"], "primary_keys": [], "count": 20469, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "police_stops_rollup", "columns": ["muni_id", "agency", "state", "geography", "year", "race", "n_stops", "n_searches", "n_arrests", "n_contraband", "n_citations", "search_rate", "hit_rate", "arrest_rate", "source", "source_url", "data_license", "citation", "updated_at"], "primary_keys": [], "count": 2384, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "professional_licenses", "columns": ["row_id", "state", "board", "license_type", "licensee_name", "business_name", "license_no", "status", "issue_date", "expiry_date", "disciplinary_flag", "city", "muni_id", "source", "source_url", "updated_at"], "primary_keys": [], "count": 7831348, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "property_sales", "columns": ["state", "parcel_id", "muni_id", "address", "owner", "sale_price", "sale_date", "assessed_value", "land_value", "land_use", "source", "source_url", "updated_at"], "primary_keys": [], "count": 38935, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "public_salaries", "columns": ["muni_id", "dataset_id", "record_id", "employee_name", "job_title", "department", "base_pay", "overtime", "total_pay", "year", "redacted", "source_domain", "source_url", "updated_at"], "primary_keys": [], "count": 3539791, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "roundups", "columns": ["muni_id", "week_of", "headline", "article_html", "article_md", "created_at"], "primary_keys": [], "count": 6335, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "school_finance", "columns": ["muni_id", "year", "function_code", "function_name", "amount", "updated_at"], "primary_keys": [], "count": 120160, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "school_stats", "columns": ["muni_id", "leaid", "enrollment", "teachers_fte", "schools_count", "per_pupil_spending", "revenue_total", "year", "updated_at", "read_pct_proficient", "math_pct_proficient", "frpl_pct", "assessment_year"], "primary_keys": [], "count": 965, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "service_requests_recent", "columns": ["muni_id", "dataset_id", "request_id", "category", "status", "created_date", "source_domain", "updated_at"], "primary_keys": [], "count": 100, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "service_requests_rollup", "columns": ["muni_id", "category", "period_month", "count", "source_domain", "source_url", "dataset_id", "updated_at"], "primary_keys": [], "count": 6898, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements", "columns": ["id", "candidate_id", "meeting_id", "muni_id", "city", "state", "country", "meeting_date", "body_name", "category", "claimant", "defendant", "amount", "amount_type", "case_no", "court", "incident_summary", "settlement_date", "funding_source", "quote", "snippet", "source", "source_document", "mytown_record", "model", "grounded", "dup_rank", "created_at"], "primary_keys": [], "count": 2468, "hidden": false, "fts_table": "settlements_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "staar_results", "columns": ["muni_id", "year", "grade", "subject", "approaches_pct", "meets_pct", "masters_pct", "updated_at"], "primary_keys": [], "count": 53631, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "state_bills", "columns": ["state", "session", "bill_id", "openstates_id", "title", "classification", "subjects", "status", "latest_action_date", "sponsors", "source_url", "updated_at"], "primary_keys": [], "count": 1454904, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "state_legislators", "columns": ["openstates_id", "state", "name", "party", "district", "chamber", "current", "source_url", "updated_at"], "primary_keys": [], "count": 21596, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "state_votes", "columns": ["vote_id", "state", "session", "bill_id", "motion", "classification", "result", "vote_date", "chamber", "yes_count", "no_count", "other_count", "source_url", "updated_at", "member_vote_count"], "primary_keys": [], "count": 1175161, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "surveillance_spending", "columns": ["vendor", "city", "state", "spend_date", "product", "amount", "quote", "source_document", "mytown_record", "ledger", "amount_type", "dup_rank", "geo_suspect", "anomaly", "state_norm"], "primary_keys": [], "count": 4390, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "usda_rd_properties", "columns": ["borrower_id", "project_id", "project_check_digit", "mfis_key", "muni_id", "match_method", "place_geoid", "cousub_geoid", "county_fips", "report_date", "property_name", "city", "state", "zip", "latitude", "longitude", "total_units", "vacant_units", "rental_assistance_units", "rental_type", "section_program", "revitalization", "tax_credit", "tax_credit_expires", "management_name", "borrower_name", "borrower_type", "borrower_city_state", "estimated_exit_date", "estimated_exit_year", "restrictive_clause_expires_year", "loan_payoff_year", "prepay_eligible", "prepay_eligible_year", "fy_of_loan_obligation", "interest_rate_at_closing", "loan_amount", "balloon_payment", "remaining_term_days", "orig_loan_term_years", "natural_maturity_date", "upb_maturity_date", "date_of_operation", "source", "source_url", "data_license", "updated_at"], "primary_keys": [], "count": 12420, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "warn_notices", "columns": ["uid", "state", "employer", "city", "county", "muni_id", "num_affected", "notice_date", "effective_date", "layoff_type", "reason", "source", "source_url", "updated_at"], "primary_keys": [], "count": 2827, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "water_violations", "columns": ["muni_id", "pwsid", "system_name", "state", "city_served", "county_served", "population_served", "year", "violation_count", "health_based_count", "source_url", "data_license", "updated_at"], "primary_keys": [], "count": 32661, "hidden": false, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "briefs_fts", "columns": ["headline", "summary", "briefs_fts", "rank"], "primary_keys": [], "count": 1318271, "hidden": true, "fts_table": "briefs_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "briefs_fts_config", "columns": ["k", "v"], "primary_keys": ["k"], "count": 1, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "briefs_fts_data", "columns": ["id", "block"], "primary_keys": ["id"], "count": 68764, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "briefs_fts_docsize", "columns": ["id", "sz"], "primary_keys": ["id"], "count": 1318271, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "briefs_fts_idx", "columns": ["segid", "term", "pgno"], "primary_keys": ["segid", "term"], "count": 18382, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "decisions_fts", "columns": ["headline", "summary", "decisions_fts", "rank"], "primary_keys": [], "count": 486268, "hidden": true, "fts_table": "decisions_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "decisions_fts_config", "columns": ["k", "v"], "primary_keys": ["k"], "count": 1, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "decisions_fts_data", "columns": ["id", "block"], "primary_keys": ["id"], "count": 27493, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "decisions_fts_docsize", "columns": ["id", "sz"], "primary_keys": ["id"], "count": 486268, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "decisions_fts_idx", "columns": ["segid", "term", "pgno"], "primary_keys": ["segid", "term"], "count": 10620, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "meeting_attachments_fts", "columns": ["item_title", "text", "meeting_attachments_fts", "rank"], "primary_keys": [], "count": 691746, "hidden": true, "fts_table": "meeting_attachments_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "meeting_attachments_fts_config", "columns": ["k", "v"], "primary_keys": ["k"], "count": 1, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "meeting_attachments_fts_data", "columns": ["id", "block"], "primary_keys": ["id"], "count": 334287, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "meeting_attachments_fts_docsize", "columns": ["id", "sz"], "primary_keys": ["id"], "count": 691746, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "meeting_attachments_fts_idx", "columns": ["segid", "term", "pgno"], "primary_keys": ["segid", "term"], "count": 92530, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "member_votes_fts", "columns": ["motion", "member_name", "member_votes_fts", "rank"], "primary_keys": [], "count": 4819245, "hidden": true, "fts_table": "member_votes_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "member_votes_fts_config", "columns": ["k", "v"], "primary_keys": ["k"], "count": 1, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "member_votes_fts_data", "columns": ["id", "block"], "primary_keys": ["id"], "count": 33397, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "member_votes_fts_docsize", "columns": ["id", "sz"], "primary_keys": ["id"], "count": 4819245, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "member_votes_fts_idx", "columns": ["segid", "term", "pgno"], "primary_keys": ["segid", "term"], "count": 14596, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements_fts", "columns": ["claimant", "defendant", "incident_summary", "quote", "settlements_fts", "rank"], "primary_keys": [], "count": 2468, "hidden": true, "fts_table": "settlements_fts", "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements_fts_config", "columns": ["k", "v"], "primary_keys": ["k"], "count": 1, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements_fts_data", "columns": ["id", "block"], "primary_keys": ["id"], "count": 131, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements_fts_docsize", "columns": ["id", "sz"], "primary_keys": ["id"], "count": 2468, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}, {"name": "settlements_fts_idx", "columns": ["segid", "term", "pgno"], "primary_keys": ["segid", "term"], "count": 113, "hidden": true, "fts_table": null, "foreign_keys": {"incoming": [], "outgoing": []}, "private": false}], "hidden_count": 25, "views": [], "queries": [{"title": "New Orleans: what a public body paid a vendor (try: amazon, meta, entergy)", "description": "Every payment line New Orleans bodies filed, searchable by vendor. Source is each body's own transparency file, and `source_url` on every row links back to it. CAUTION ON NAME SEARCH: card-processor descriptors do not look like company names. Meta's charges appear as `FACEBK *W6U9B45J52` with the purpose \"BOOSTED FACEBOOK ADS\", so a payee search for \"meta\" MISSES them and instead returns scrap METAL companies and businesses in METAIRIE. Search `purpose` as well as `payee`.\n", "sql": "SELECT mu.name AS body, g.payee, g.purpose, g.amount, g.txn_date, g.source_url\nFROM gov_payments g JOIN municipalities mu ON mu.id = g.muni_id\nWHERE mu.state = 'LA'\n  AND (lower(g.payee) LIKE '%' || lower(:vendor) || '%'\n       OR lower(g.purpose) LIKE '%' || lower(:vendor) || '%')\nORDER BY g.amount DESC NULLS LAST\nLIMIT 500", "name": "nola_vendor_payments", "private": false}, {"title": "Louisiana: who is registered to lobby for a company (try: meta platforms, entergy)", "description": "Louisiana Board of Ethics lobbyist registrations. `branch` tells you whether the registration covers LOCAL government as well as the legislature and executive. Louisiana publishes NO exact compensation on these filings, only a paid yes/no, so this answers WHO and WHEN, never how much. Match on the full company name: searching \"meta\" alone returns a lobbying client called Meta Traffic and hundreds of unrelated METAL and METAIRIE rows.\n", "sql": "SELECT client_name, lobbyist_name, year, branch, paid, date_from, date_to, source_url\nFROM lobbying_registrations\nWHERE state = 'LA'\n  AND lower(client_name) LIKE '%' || lower(:client) || '%'\nORDER BY year DESC, lobbyist_name\nLIMIT 500", "name": "la_lobbyists_for_client", "private": false}, {"title": "Louisiana: what lobbyists reported spending on a named official (try: new orleans)", "description": "Louisiana lobbyist expenditure reports, filtered by the STATE'S OWN label for the recipient's office, so searching \"new orleans\" returns city officials rather than everyone whose surname happens to match. TWO LIMITS THAT DECIDE WHAT YOU CAN WRITE. These reports are filed per LOBBYIST and name no client, so a total belongs to the lobbyist across all their clients, never to one company. And when the recipient is a named individual the filing carries no event, venue or description at all, while group recipients (a caucus, a delegation) usually do.\n", "sql": "SELECT recipient_name, recipient_role, lobbyist_name, amount, year, description\nFROM lobbying_expenditures\nWHERE state = 'LA'\n  AND lower(coalesce(recipient_role,'')) LIKE '%' || lower(:office) || '%'\nORDER BY amount DESC NULLS LAST\nLIMIT 500", "name": "la_spending_on_officials", "private": false}, {"title": "Federal PAC money into one state (try: LA, then filter by committee)", "description": "Complete committee-to-candidate contributions from the FEC bulk files, all cycles 2010-2026, no row cap. This is the full denominator, which is what makes an ABSENCE here meaningful. Keyed on the FEC committee id rather than the name, because committees get renamed: Meta's PAC (C00502906) filed as FACEBOOK INC PAC before 2022. `txn_type` distinguishes direct contributions from independent expenditures, which are legally different and must not be summed together. `office` shows the recipient's seat as H-LA-01 or S-LA. The `state` column here is the recipient's OFFICE state, not a donor address.\n", "sql": "SELECT filer_name AS pac, filer_id AS committee_id,\n       counterparty_name AS recipient, office, amount, txn_date, txn_type\nFROM cf_transactions\nWHERE source = 'fec_bulk_pas2'\n  AND state = upper(:state)\nORDER BY amount DESC NULLS LAST\nLIMIT 500", "name": "pac_money_to_state", "private": false}, {"title": "Surveillance tech: line items for one vendor (try: axon, flock, clearview)", "description": "DISCOVERY INDEX, NOT A SPENDING TOTAL. Each row is one dollar figure found in one meeting record, with a verbatim quote and a link to the source document. The SAME procurement usually appears several times (committee, council, approval, amendment, renewal), so DO NOT SUM this column. Read `amount_type`: `ceiling` means \"not to exceed\" (an authorization cap, not money paid). `dup_rank` > 1 marks a redundant copy. `geo_suspect` = 1 means the city attribution disagrees with the source link. `anomaly` = 1 means the figure is implausible for that jurisdiction and needs review.\n", "sql": "SELECT vendor, city, state_norm AS state, spend_date, product,\n       amount, amount_type, dup_rank, geo_suspect, anomaly,\n       quote, source_document\nFROM surveillance_spending\nWHERE lower(vendor) LIKE '%' || lower(:vendor) || '%'\nORDER BY amount DESC NULLS LAST\nLIMIT 500", "name": "surveillance_by_vendor", "private": false}, {"title": "Reporter search: a surveillance vendor across towns and time", "description": "Start with vendor=flock, axon, or motorola; optionally narrow by city, two-letter state, and earliest date. This returns the complete matching timeline (up to the site's 2,000-row safety limit), including the supporting quote and primary-document link. It is a discovery index, not a payment ledger: do not sum the amounts. A ceiling is an authorization cap, and dup_rank above 1 is a repeated appearance of the same procurement. Search the vendor's legal name and product names separately when doing exhaustive work.\n", "sql": "SELECT city, state_norm AS state, spend_date, vendor, product,\n       amount, amount_type, dup_rank, geo_suspect, anomaly,\n       quote, source_document, mytown_record\nFROM surveillance_spending\nWHERE lower(COALESCE(vendor, '')) LIKE '%' || lower(:vendor) || '%'\n  AND (:city = '' OR lower(COALESCE(city, '')) LIKE '%' || lower(:city) || '%')\n  AND (:state = '' OR state_norm = upper(:state))\n  AND (:from_date = '' OR spend_date >= :from_date)\nORDER BY state_norm, city, spend_date, vendor", "name": "surveillance_vendor_timeline", "private": false}, {"title": "Reporter search: surveillance company family (parent + acquired brands)", "description": "Search an ecosystem rather than one invoice spelling. Supported families are axon, motorola, flock, soundthinking, magnet, securus, and viapath. For example, axon also searches TASER, Evidence.com, Fusus, Dedrone and VieVu; motorola also searches Vigilant, Avigilon and WatchGuard. Results remain leads, not a spending total: one procurement can recur at several stages and a parent company can sell non-surveillance products.\n", "sql": "WITH family_terms(family, term) AS (\n  VALUES\n    ('axon','axon'), ('axon','taser'), ('axon','evidence.com'),\n    ('axon','fusus'), ('axon','dedrone'), ('axon','vievu'),\n    ('motorola','motorola'), ('motorola','vigilant'),\n    ('motorola','avigilon'), ('motorola','watchguard'),\n    ('flock','flock'), ('flock','raven'), ('flock','condor'),\n    ('flock','aerodome'),\n    ('soundthinking','soundthinking'), ('soundthinking','shotspotter'),\n    ('soundthinking','crimetracer'), ('soundthinking','coplink'),\n    ('soundthinking','plateranger'),\n    ('magnet','magnet forensics'), ('magnet','graykey'),\n    ('magnet','grayshift'),\n    ('securus','securus'), ('securus','aventiv'),\n    ('viapath','viapath'), ('viapath','global tel'), ('viapath','gtl')\n)\nSELECT DISTINCT s.city, s.state_norm AS state, s.spend_date, s.vendor, s.product,\n       s.amount, s.amount_type, s.dup_rank, s.geo_suspect, s.anomaly,\n       s.quote, s.source_document\nFROM surveillance_spending AS s\nJOIN family_terms AS f\n  ON lower(COALESCE(s.vendor,'') || ' ' || COALESCE(s.product,'') || ' ' ||\n           COALESCE(s.quote,'')) LIKE '%' || f.term || '%'\nWHERE f.family = lower(:company)\n  AND (:state = '' OR s.state_norm = upper(:state))\n  AND (:from_date = '' OR s.spend_date >= :from_date)\nORDER BY s.state_norm, s.city, s.spend_date, s.vendor", "name": "surveillance_company_family", "private": false}, {"title": "Reporter notebook: surveillance expansion, switching, and intercept leads", "description": "A reproducible notebook of high-value leads involving vendor expansion, competing or bundled systems, and unusual interception technology. Includes Flock activity, Salinas's later Vigilant purchase, Axon/Flock records in Vallejo, and Rialto's cell-site simulator. These are selected leads, not a representative sample or aggregate.\n", "sql": "SELECT city, state_norm AS state, spend_date, vendor, product,\n       amount, amount_type, dup_rank, geo_suspect, anomaly,\n       quote, source_document\nFROM surveillance_spending\nWHERE (city IN ('San Marino','Dayton','Fort Worth','Oakland','Berkeley','Salinas','Vallejo')\n       AND (lower(vendor) LIKE '%flock%' OR lower(vendor) LIKE '%vigilant%'\n            OR lower(vendor) LIKE '%axon%'))\n   OR lower(COALESCE(product,'')) LIKE '%cell site simulator%'\n   OR lower(COALESCE(quote,'')) LIKE '%cell site simulator%'\nORDER BY state_norm, city, spend_date, vendor", "name": "surveillance_story_leads", "private": false}, {"title": "Reporter search: unusual surveillance technology", "description": "Search both the extracted product description and vendor name. Useful terms include ALPR, body camera, face recognition, drone, gunshot, CellHawk, cell site simulator, and StingRay. This is intentionally a lead generator. Open the source document before describing the technology: company names such as Motorola and L3Harris also appear on ordinary radios, dispatch systems, and unrelated municipal software.\n", "sql": "SELECT city, state_norm AS state, spend_date, vendor, product,\n       amount, amount_type, dup_rank, geo_suspect, anomaly,\n       quote, source_document, ledger\nFROM surveillance_spending\nWHERE (lower(COALESCE(product, '')) LIKE '%' || lower(:term) || '%'\n       OR lower(COALESCE(vendor, '')) LIKE '%' || lower(:term) || '%'\n       OR lower(COALESCE(quote, '')) LIKE '%' || lower(:term) || '%')\n  AND (:state = '' OR state_norm = upper(:state))\nORDER BY state_norm, city, spend_date, vendor", "name": "surveillance_by_technology", "private": false}, {"title": "Surveillance tech: the CONSERVATIVE total (deduped, stated amounts only)", "description": "The only aggregate on this site that should be quoted. It keeps one row per duplicate group (`dup_rank` = 1), counts only figures actually stated as an amount (excludes \"not to exceed\" ceilings, proposed and recommended items), and drops rows flagged as anomalies or with suspect city attribution. It also excludes the non-surveillance ledgers (two-way radios, records/CAD software, fingerprint biometrics). Even this is a floor, not a precise number: it cannot tell an amendment from an original award.\n", "sql": "SELECT\n  count(*)                             AS line_items,\n  count(DISTINCT city || '|' || state_norm) AS governments,\n  count(DISTINCT vendor)               AS vendors,\n  round(sum(amount), 2)                AS conservative_total\nFROM surveillance_spending\nWHERE dup_rank = 1\n  AND amount_type = 'stated'\n  AND COALESCE(anomaly, 0) = 0\n  AND COALESCE(geo_suspect, 0) = 0\n  AND ledger NOT LIKE 'sv:radio_infra:%'\n  AND ledger NOT LIKE 'sv:rms:%'\n  AND ledger NOT LIKE 'sv:biometrics:%'\n  AND ledger NOT LIKE 'sv:not_surveillance:%'\n  AND ledger NOT LIKE 'sv:police_equipment:%'", "name": "surveillance_defensible_total", "private": false}, {"title": "Surveillance tech: data-quality report (read this before quoting anything)", "description": "What is wrong with this table, counted. An external audit on 2026-07-29 found the aggregate pages were summing amounts that must not be summed. These are the flags added in response.\n", "sql": "SELECT 'exact/near duplicate rows'        AS issue, count(*) AS rows\n  FROM surveillance_spending WHERE dup_rank > 1\nUNION ALL SELECT 'ceilings (\"not to exceed\"), not payments', count(*)\n  FROM surveillance_spending WHERE amount_type = 'ceiling'\nUNION ALL SELECT 'proposed / recommended, not approved', count(*)\n  FROM surveillance_spending WHERE amount_type IN ('proposed','recommended')\nUNION ALL SELECT 'estimated amounts', count(*)\n  FROM surveillance_spending WHERE amount_type = 'estimated'\nUNION ALL SELECT 'city attribution disagrees with source link', count(*)\n  FROM surveillance_spending WHERE geo_suspect = 1\nUNION ALL SELECT 'implausible amount, needs manual review', count(*)\n  FROM surveillance_spending WHERE anomaly = 1", "name": "surveillance_data_quality", "private": false}, {"title": "Surveillance tech: totals by technology category", "description": "Every line item grouped by what the technology actually is (ALPR, body cameras, gunshot detection, face recognition, data fusion/OSINT, phone forensics, drones, cameras, cell-site interception, photo enforcement, jail-call monitoring, student monitoring \u2014 plus the not-surveillance categories radio_infra and rms, shown so they can be excluded).\n", "sql": "SELECT CASE WHEN ledger LIKE 'sv:%'\n            THEN substr(ledger, 4, instr(substr(ledger,4), ':') - 1)\n            ELSE ledger END AS category,\n       count(*) AS line_items,\n       count(DISTINCT vendor) AS vendors,\n       count(DISTINCT city || state) AS governments,\n       round(sum(amount),2) AS conservative_total\nFROM surveillance_spending\nWHERE dup_rank = 1 AND amount_type = 'stated'\n  AND COALESCE(anomaly,0)=0 AND COALESCE(geo_suspect,0)=0\n  AND ledger NOT LIKE 'sv:radio_infra:%' AND ledger NOT LIKE 'sv:rms:%'\n  AND ledger NOT LIKE 'sv:biometrics:%' AND ledger NOT LIKE 'sv:not_surveillance:%'\n  AND ledger NOT LIKE 'sv:police_equipment:%'\nGROUP BY category\nORDER BY conservative_total DESC NULLS LAST", "name": "surveillance_by_category", "private": false}, {"title": "Surveillance tech: largest dollar figures found (NOT confirmed payments)", "description": "The largest amounts appearing in meeting records. These are NOT confirmed payments. Check `amount_type` on every row before using it: `ceiling` is a \"not to exceed\" authorization cap, `proposed` and `recommended` never reached a final vote, and `anomaly` = 1 flags figures implausible for that jurisdiction. Verify against the linked source document before publishing any single number.\n", "sql": "SELECT amount, amount_type, anomaly, geo_suspect, dup_rank,\n       vendor, city, state_norm AS state, spend_date, product,\n       quote, source_document\nFROM surveillance_spending\nWHERE amount IS NOT NULL\nORDER BY amount DESC\nLIMIT 200", "name": "surveillance_biggest", "private": false}, {"title": "Surveillance tech: by state (conservative, deduped)", "description": "Deduped, stated-amounts-only totals by state, excluding ceilings, proposed items, anomalies, suspect geography, and the non-surveillance ledgers. This is a floor: it still cannot distinguish an amendment from an original award.\n", "sql": "SELECT state_norm AS state,\n       count(*) AS line_items,\n       count(DISTINCT city || '|' || state_norm) AS governments,\n       round(sum(amount),2) AS conservative_total\nFROM surveillance_spending\nWHERE dup_rank = 1 AND amount_type = 'stated'\n  AND COALESCE(anomaly,0)=0 AND COALESCE(geo_suspect,0)=0\n  AND ledger NOT LIKE 'sv:radio_infra:%' AND ledger NOT LIKE 'sv:rms:%'\n  AND ledger NOT LIKE 'sv:biometrics:%' AND ledger NOT LIKE 'sv:not_surveillance:%'\n  AND ledger NOT LIKE 'sv:police_equipment:%'\nGROUP BY state\nORDER BY conservative_total DESC NULLS LAST", "name": "surveillance_by_state", "private": false}, {"title": "Surveillance tech: everything one city bought (search by city)", "description": "Every confirmed surveillance-spending line item for a single local government.", "sql": "SELECT spend_date, vendor, product, amount, quote, source_document\nFROM surveillance_spending\nWHERE lower(city) LIKE '%' || lower(:city) || '%'\nORDER BY spend_date DESC", "name": "surveillance_in_city", "private": false}, {"title": "Vendor awards, contracts and payments (federal + local, DO NOT SUM)", "description": "Search FEDERAL awards and LOCALLY published contract/payment records by vendor name. These have different financial meanings and must not be added together. \u26a0 FEDERAL ROWS ARE NOT SPENDING BY THE LISTED PLACE. When source_level = 'federal_award' the place reflects where USAspending geographically associated the award (place of performance or recipient location) \u2014 that local government did not fund, approve, or purchase it. The exact geolocation method varies by source record READ `payer_level`: `federal` means USAspending geographically associated the award with that place (place of performance or recipient location) and the local government did NOT fund, approve or purchase it; `municipal` means the local government published the record itself, so the place IS the payer. Filter on payer_level before writing \"town X paid Y\". \u26a0 READ `record_type` and NEVER sum across values: federal_contract/federal_grant are obligations, 'contract' is a contract value (often a ceiling, and amendments may replace rather than add to a prior figure), 'expenditure'/'disbursement' are closer to money actually paid. \u26a0 VENDOR MATCH IS A SUBSTRING, so short names produce false positives (\"axon\" also matches \"Saxon\"). Check payee_raw on every row. \u26a0 SHOWING ONLY THE 500 LARGEST MATCHES \u2014 this is not a complete result set and its sum is not a total. Run \"vendor totals by record type\" for full counts before quoting anything.\n", "sql": "SELECT\n  m.name AS place_name,\n  m.kind AS place_type,\n  gp.state,\n  CASE WHEN gp.source = 'usaspending' THEN 'federal_award'\n       ELSE 'local_record' END AS source_level,\n  gp.payer_level,\n  gp.record_type,\n  gp.payee AS payee_raw,\n  gp.amount,\n  gp.txn_date,\n  gp.end_date,\n  gp.category,\n  gp.purpose,\n  gp.funding_source,\n  gp.source,\n  gp.external_id,\n  gp.source_url,\n  gp.muni_id\nFROM gov_payments gp\nLEFT JOIN municipalities m ON m.id = gp.muni_id\nWHERE trim(COALESCE(:vendor,'')) <> ''\n  AND lower(gp.payee) LIKE '%' || lower(trim(:vendor)) || '%'\nORDER BY CAST(NULLIF(replace(replace(gp.amount,'$',''),',',''),'') AS REAL) DESC\nLIMIT 500", "name": "vendor_payments", "private": false}, {"title": "Vendor totals by record type (run this BEFORE quoting any vendor total)", "description": "Complete counts for a vendor across ALL matching rows, split by federal vs local and by record type, so you can see what the 500-row vendor page is truncating and never sum across categories that mean different things. federal_award rows are NOT local spending.\n", "sql": "SELECT\n  CASE WHEN gp.source = 'usaspending' THEN 'federal_award'\n       ELSE 'local_record' END AS source_level,\n  gp.record_type,\n  gp.payer_level,\n  count(*) AS matching_rows,\n  count(DISTINCT gp.muni_id) AS places,\n  round(sum(CAST(NULLIF(replace(replace(gp.amount,'$',''),',',''),'') AS REAL)), 2) AS sum_of_amounts,\n  min(gp.txn_date) AS earliest,\n  max(gp.txn_date) AS latest\nFROM gov_payments gp\nWHERE trim(COALESCE(:vendor,'')) <> ''\n  AND lower(gp.payee) LIKE '%' || lower(trim(:vendor)) || '%'\nGROUP BY source_level, gp.record_type, gp.payer_level\nORDER BY sum_of_amounts DESC", "name": "vendor_totals_by_record_type", "private": false}, {"title": "How a town's council voted (search by town name)", "sql": "SELECT mu.name AS town, mu.state, mv.body_name, mv.motion, mv.member_name, mv.vote\nFROM member_votes mv JOIN municipalities mu ON mu.id = mv.muni_id\nWHERE lower(mu.name) LIKE '%' || lower(:town) || '%'\nORDER BY mv.meeting_id DESC LIMIT 1000", "name": "how_a_town_voted", "private": false}, {"title": "Search the staff-report text (find buried unit counts, dollar figures)", "sql": "SELECT ma.meeting_id, mu.name AS town, mu.state, ma.item_title,\n       substr(ma.text,1,320) AS excerpt, ma.source_url\nFROM meeting_attachments ma\nLEFT JOIN meetings m ON m.id = ma.meeting_id\nLEFT JOIN municipalities mu ON mu.id = m.muni_id\nWHERE ma.source_url <> '__done__' AND ma.text LIKE '%' || :keyword || '%'\nLIMIT 300", "name": "search_staff_reports", "private": false}, {"title": "Largest campaign contributions to a recipient", "sql": "SELECT state, filer_name AS recipient, counterparty_name AS donor, employer,\n       amount, txn_date, election_cycle\nFROM cf_transactions\nWHERE filer_name LIKE :recipient || '%'\nORDER BY amount DESC LIMIT 500", "name": "biggest_contributions", "private": false}, {"title": "A Texas district's STAAR %Meets over time (search by district)", "sql": "SELECT mu.name AS district, s.year, s.grade, s.subject, s.meets_pct\nFROM staar_results s JOIN municipalities mu ON mu.id = s.muni_id\nWHERE lower(mu.name) LIKE '%' || lower(:district) || '%'\nORDER BY s.subject, s.grade, s.year", "name": "texas_staar_trend", "private": false}, {"title": "A Texas district's spending by category, latest year (search by district)", "description": "Same URL and same result as before, rewritten 2026-07-30: the original ran a correlated \"latest year\" subquery once per candidate row and hit the 9-second query limit.\n", "sql": "WITH d AS (\n  SELECT id, name FROM municipalities\n  WHERE lower(name) LIKE '%' || lower(:district) || '%'\n), y AS (\n  SELECT muni_id, max(year) AS yr FROM school_finance\n  WHERE muni_id IN (SELECT id FROM d) GROUP BY muni_id\n)\nSELECT d.name AS district, f.year, f.function_code, f.function_name, f.amount\nFROM school_finance f\nJOIN y ON y.muni_id = f.muni_id AND y.yr = f.year\nJOIN d ON d.id = f.muni_id\nORDER BY f.amount DESC", "name": "texas_school_spending_by_category", "private": false}, {"title": "A school district's board decisions next to its proficiency (search by district)", "sql": "SELECT mu.name AS district, mu.state, ss.read_pct_proficient, ss.math_pct_proficient,\n       ss.per_pupil_spending, d.headline AS board_decision, m.meeting_date\nFROM municipalities mu\nLEFT JOIN school_stats ss ON ss.muni_id = mu.id\nLEFT JOIN meetings m ON m.muni_id = mu.id\nLEFT JOIN decisions d ON d.meeting_id = m.id\nWHERE mu.kind='school' AND lower(mu.name) LIKE '%' || lower(:district) || '%'\nORDER BY m.meeting_date DESC LIMIT 200", "name": "school_board_and_scores", "private": false}, {"title": "Towns with a RECORDED VOTE adopting a data center moratorium (blank = all)", "description": "A verified floor, not a census. Every row required an explicit passage record in the town's own minutes: a vote tally, \"unanimous\", or \"motion carried\" alongside the adopting verb. An earlier cut of 97 was rejected because 51 of those rows quoted an AGENDA ITEM TITLE rather than an outcome, 9 referred to a moratorium adopted elsewhere, and 2 were a committee recommendation or a first reading. A moratorium is a temporary pause on accepting applications while zoning is written. It is NOT a rejection of a data center, and must never be described as one.", "sql": "SELECT city, state, adopted_date, evidence, mytown_page\nFROM datacenter_moratoriums\nWHERE (:state = '' OR state = upper(:state))\nORDER BY adopted_date DESC", "name": "datacenter_moratoriums", "private": false}], "allow_execute_sql": true, "query_ms": 273.2855709909927, "source": "MyTown", "source_url": "https://mytown.theboringparts.com", "license": "CC BY 4.0", "license_url": "https://creativecommons.org/licenses/by/4.0/"}