Datasets:

AFOS-Analytics1
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usa-2024-electoral-divergence

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-# Data Dictionary — AFOS USA 2024 Electoral Divergence
-> 🌐 **EN** — Data dictionary for the AFOS USA 2024 electoral-divergence dataset (polls × prediction markets × press). · **PT** — Dicionário de dados do dataset AFOS EUA 2024 (pesquisas × mercados de previsão × imprensa). · **ES** — Diccionario de datos del dataset AFOS EE. UU. 2024 (encuestas × mercados de predicción × prensa).
-> Column names and definitions below are kept in **English** (CSV/academic standard). · Os nomes e definições de coluna seguem em **inglês** (padrão dos CSVs). · Los nombres y definiciones se mantienen en **inglés**.
-Poll figures trace to a named pollster's published release, compiled from **FiveThirtyEight's** public 2024 president-poll database (Wayback snapshot of 4 Nov 2024). Market odds come from public Polymarket markets; press anchors are public articles archived in the Wayback Machine. Nothing is imputed or smoothed; missing values are left **blank**.
-## `polls/usa-national-polls.csv` (long format)
-One row per candidate per poll. National general-election polls only (state = blank, stage = general, cycle = 2024), Harris & Trump. 3,691 rows.
-| Column | Type | Notes |
-|--------|------|-------|
-| `poll_id` | integer | FiveThirtyEight poll identifier. |
-| `pollster` | string | Polling firm (e.g. "Siena/NYT", "Marquette Law School", "Emerson"). |
-| `end_date` | date | End of fieldwork (`YYYY-MM-DD`). |
-| `sample_size` | integer | Sample size. |
-| `population` | string | Sampled population: `lv` (likely voters), `rv` (registered voters), `a` (all adults). |
-| `numeric_grade` | number | FiveThirtyEight pollster quality rating (0–3 scale), where published. |
-| `methodology` | string | Survey mode (e.g. "Online Panel", "Live Phone", "IVR/Online"). |
-| `candidate` | string | `Harris` or `Trump`. |
-| `pct` | number | National voting intention for that candidate, %. |
-| `source_url` | string | Primary source URL for the poll, as recorded by FiveThirtyEight. |
-## `data/usa-winner-market-timeseries.csv` — PRIMARY AXIS (electoral college)
-Daily Polymarket win-probability from the **"Presidential Election Winner 2024"** market (who becomes president; total volume ≈ US$ 3.7 bn — the largest election market in history). 613 rows.
-| Column | Type | Notes |
-|--------|------|-------|
-| `date` | date | `YYYY-MM-DD` (daily fidelity). |
-| `candidate` | string | `Trump` or `Harris`. |
-| `win_prob_pct` | number | Implied probability of **winning the presidency**, % (0–100). |
-## `data/usa-popularvote-market-timeseries.csv` — COUNTERPOINT (popular vote)
-Daily Polymarket win-probability from the **"Popular Vote Winner 2024"** market (who wins more popular votes; total volume ≈ US$ 628 M). This is the market that favored Harris and **erred**. 615 rows. Same columns as the winner series; `win_prob_pct` = implied probability of **winning the popular vote**.
-## `data/usa-poll-aggregate-timeseries.csv`
-Trailing 7-day simple average of national poll vote share. 1,322 rows.
-| Column | Type | Notes |
-|--------|------|-------|
-| `date` | date | `YYYY-MM-DD`. |
-| `candidate` | string | `Trump` or `Harris`. |
-| `poll_vote_share_pct_7dma` | number | 7-day trailing average of national vote-share polls ending on or before `date`, %. |
-## `data/usa-divergence-timeseries.csv`
-Market × poll divergence for the Harris–Trump head-to-head period (after Biden withdrew, 21 Jul 2024). 218 rows. **Axis = the winner (electoral-college) market.**
-| Column | Type | Notes |
-|--------|------|-------|
-| `date` | date | `YYYY-MM-DD` (market date). |
-| `candidate` | string | `Trump` or `Harris`. |
-| `market_win_prob_pct` | number | Winner-market implied probability of **winning the presidency**, %. |
-| `poll_vote_share_pct` | number | National poll **vote share** (7-day trailing average), %. |
-| `naive_gap_pp` | number | `market_win_prob_pct − poll_vote_share_pct`, in percentage points. **Different units** (probability vs share): reported raw, **not scale-reconciled**. The sign and trajectory are the signal, not the magnitude. |
-## `press/usa-2024-press-timeline.csv`
-Curated, Wayback-archived press anchors cross-referencing the market×poll divergence. 7 rows.
-| Column | Type | Notes |
-|--------|------|-------|
-| `date` | date | Article publication date (`YYYY-MM-DD`). |
-| `outlet` | string | Publishing outlet (Fortune, Al Jazeera, NBC News, NPR, PBS NewsHour, CNN). |
-| `headline` | string | Exact article headline. |
-| `theme` | string | `market_poll_divergence` · `poll_near_tie` · `market_conviction_whale` · `result_validator` · `market_vindicated` · `poll_accuracy_postmortem`. |
-| `axis` | string | Which AFOS axis the anchor maps to (`market`, `poll`, `market×poll`, `result`). |
-| `tier` | string | `anchor` (core) or `secondary`. |
-| `primary_source` | string | Underlying primary source where the carrier differs (e.g. "Associated Press (race call)", "Wall Street Journal (original)"). |
-| `url` | string | Live article URL (verified HTTP 200). |
-| `wayback_url` | string | Internet Archive Wayback Machine snapshot (permanent citation). |
-## `data/usa-case-summary.json`
-Machine-readable summary of the validated case: result (electoral college + popular vote), both markets with eve-of-vote probabilities and verdict, final poll average, and the honesty note (two markets disagreed; the validator is the real result).
-## Raw provenance
-`data/usa-winner-poly-raw.json` and `data/usa-popularvote-poly-raw.json` — raw Polymarket payloads (event metadata + per-candidate daily price histories) for both markets, kept verbatim for provenance.

+# Data Dictionary — AFOS USA 2024 Electoral Divergence
+> 🌐 **EN** — Data dictionary for the AFOS USA 2024 electoral-divergence dataset (polls × prediction markets × press). · **PT** — Dicionário de dados do dataset AFOS EUA 2024 (pesquisas × mercados de previsão × imprensa). · **ES** — Diccionario de datos del dataset AFOS EE. UU. 2024 (encuestas × mercados de predicción × prensa).
+> Column names and definitions below are kept in **English** (CSV/academic standard). · Os nomes e definições de coluna seguem em **inglês** (padrão dos CSVs). · Los nombres y definiciones se mantienen en **inglés**.
+Poll figures trace to a named pollster's published release, compiled from **FiveThirtyEight's** public 2024 president-poll database (Wayback snapshot of 4 Nov 2024). Market odds come from public Polymarket markets; press anchors are public articles archived in the Wayback Machine. Nothing is imputed or smoothed; missing values are left **blank**.
+## `polls/usa-national-polls.csv` (long format)
+One row per candidate per poll. National general-election polls only (state = blank, stage = general, cycle = 2024), Harris & Trump. 3,691 rows.
+| Column | Type | Notes |
+|--------|------|-------|
+| `poll_id` | integer | FiveThirtyEight poll identifier. |
+| `pollster` | string | Polling firm (e.g. "Siena/NYT", "Marquette Law School", "Emerson"). |
+| `end_date` | date | End of fieldwork (`YYYY-MM-DD`). |
+| `sample_size` | integer | Sample size. |
+| `population` | string | Sampled population: `lv` (likely voters), `rv` (registered voters), `a` (all adults). |
+| `numeric_grade` | number | FiveThirtyEight pollster quality rating (0–3 scale), where published. |
+| `methodology` | string | Survey mode (e.g. "Online Panel", "Live Phone", "IVR/Online"). |
+| `candidate` | string | `Harris` or `Trump`. |
+| `pct` | number | National voting intention for that candidate, %. |
+| `source_url` | string | Primary source URL for the poll, as recorded by FiveThirtyEight. |
+## `data/usa-winner-market-timeseries.csv` — PRIMARY AXIS (electoral college)
+Daily Polymarket win-probability from the **"Presidential Election Winner 2024"** market (who becomes president; total volume ≈ US$ 3.7 bn — the largest election market in history). 613 rows.
+| Column | Type | Notes |
+|--------|------|-------|
+| `date` | date | `YYYY-MM-DD` (daily fidelity). |
+| `candidate` | string | `Trump` or `Harris`. |
+| `win_prob_pct` | number | Implied probability of **winning the presidency**, % (0–100). |
+## `data/usa-popularvote-market-timeseries.csv` — COUNTERPOINT (popular vote)
+Daily Polymarket win-probability from the **"Popular Vote Winner 2024"** market (who wins more popular votes; total volume ≈ US$ 628 M). This is the market that favored Harris and **erred**. 615 rows. Same columns as the winner series; `win_prob_pct` = implied probability of **winning the popular vote**.
+## `data/usa-poll-aggregate-timeseries.csv`
+Trailing 7-day simple average of national poll vote share. 1,322 rows.
+| Column | Type | Notes |
+|--------|------|-------|
+| `date` | date | `YYYY-MM-DD`. |
+| `candidate` | string | `Trump` or `Harris`. |
+| `poll_vote_share_pct_7dma` | number | 7-day trailing average of national vote-share polls ending on or before `date`, %. |
+## `data/usa-divergence-timeseries.csv`
+Market × poll divergence for the Harris–Trump head-to-head period (after Biden withdrew, 21 Jul 2024). 218 rows. **Axis = the winner (electoral-college) market.**
+| Column | Type | Notes |
+|--------|------|-------|
+| `date` | date | `YYYY-MM-DD` (market date). |
+| `candidate` | string | `Trump` or `Harris`. |
+| `market_win_prob_pct` | number | Winner-market implied probability of **winning the presidency**, %. |
+| `poll_vote_share_pct` | number | National poll **vote share** (7-day trailing average), %. |
+| `naive_gap_pp` | number | `market_win_prob_pct − poll_vote_share_pct`, in percentage points. **Different units** (probability vs share): reported raw, **not scale-reconciled**. The sign and trajectory are the signal, not the magnitude. |
+## `press/usa-2024-press-timeline.csv`
+Curated, Wayback-archived press anchors cross-referencing the market×poll divergence. 7 rows.
+| Column | Type | Notes |
+|--------|------|-------|
+| `date` | date | Article publication date (`YYYY-MM-DD`). |
+| `outlet` | string | Publishing outlet (Fortune, Al Jazeera, NBC News, NPR, PBS NewsHour, CNN). |
+| `headline` | string | Exact article headline. |
+| `theme` | string | `market_poll_divergence` · `poll_near_tie` · `market_conviction_whale` · `result_validator` · `market_vindicated` · `poll_accuracy_postmortem`. |
+| `axis` | string | Which AFOS axis the anchor maps to (`market`, `poll`, `market×poll`, `result`). |
+| `tier` | string | `anchor` (core) or `secondary`. |
+| `primary_source` | string | Underlying primary source where the carrier differs (e.g. "Associated Press (race call)", "Wall Street Journal (original)"). |
+| `url` | string | Live article URL (verified HTTP 200). |
+| `wayback_url` | string | Internet Archive Wayback Machine snapshot (permanent citation). |
+## `data/usa-case-summary.json`
+Machine-readable summary of the validated case: result (electoral college + popular vote), both markets with eve-of-vote probabilities and verdict, final poll average, and the honesty note (two markets disagreed; the validator is the real result).
+## Raw provenance
+`data/usa-winner-poly-raw.json` and `data/usa-popularvote-poly-raw.json` — raw Polymarket payloads (event metadata + per-candidate daily price histories) for both markets, kept verbatim for provenance.
+## `data/usa-structural-context.csv`
+Structural country context from the **World Bank**, complementary to the divergence data: it frames the country, it does **not** predict the electoral outcome. Long/tidy format, one row per indicator, latest available year per indicator.
+| Column | Type | Notes |
+|--------|------|-------|
+| `category` | string | `governance`, `economy`, or `education`. |
+| `indicator` | string | Machine code (e.g. `political_stability`, `gdp_usd`, `expected_years_schooling`). |
+| `label` | string | Human-readable indicator name (English). |
+| `value` | number | Governance on a 0-100 scale; economy in US$ / %; education in % of GDP or years. |
+| `unit` | string | `index_0_100`, `USD`, `percent`, or `years`. |
+| `year` | integer | Reference year of the value (latest available). |
+| `source` | string | World Bank WGI (governance, via Data360) or WDI (economy & education). |
+| `iso3` | string | ISO 3166 alpha-3 country code. |
+Both sources are open-licensed (CC BY 4.0) and keyless. Governance = Worldwide Governance Indicators; economy & education = World Development Indicators.

data/usa-structural-context.csv ADDED Viewed

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+category,indicator,label,value,unit,year,source,iso3
+governance,political_stability,"Political stability",64.3,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+governance,voice_accountability,"Voice and accountability",72.4,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+governance,rule_of_law,"Rule of law",73.5,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+governance,government_effectiveness,"Government effectiveness",77.8,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+governance,regulatory_quality,"Regulatory quality",76.2,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+governance,control_of_corruption,"Control of corruption",69.9,index_0_100,2024,"World Bank Worldwide Governance Indicators (WGI)",USA
+macro,gdp_usd,"GDP (current US$)",28750956130731,USD,2024,"World Bank World Development Indicators (WDI)",USA
+macro,gdp_per_capita_usd,"GDP per capita (current US$)",84534.04,USD,2024,"World Bank World Development Indicators (WDI)",USA
+macro,inflation_pct,"Inflation, consumer prices (annual %)",2.95,percent,2024,"World Bank World Development Indicators (WDI)",USA
+education,gov_expenditure_pct_gdp,"Government expenditure on education (% of GDP)",5.42,percent,2021,"World Bank World Development Indicators (WDI)",USA
+education,expected_years_schooling,"Expected years of schooling",16.28,years,2018,"World Bank World Development Indicators (WDI)",USA