DATA_DICTIONARY.md

Data Dictionary — AFOS Brazil 2026 Electoral Divergence

Every file, every column, with type, unit, and provenance. Values are never imputed or smoothed: a missing value is left blank, not filled.

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polls/tse-registry.csv / .json

Official TSE poll-registration registry for the 2026 presidential cycle, built directly from the TSE Open Data file pesquisa_eleitoral_2026_BRASIL.csv (dadosabertos.tse.jus.br). One row per registered presidential poll (365 at the latest snapshot; the count grows as new polls are registered). This is the full set of public registration fields — every poll registered in Brazil must, by Lei 9.504/1997 art. 33 (and Resolução TSE 23.600/2019), disclose its methodology, sampling/weighting design, cost, contracting party and responsible statistician before release. The registry carries that design; it does not carry per-candidate results (the institute publishes those) nor the demographic crosstabs of the results.

Column	Type	Unit / format	Notes
register_tse	string	e.g. BR042272026	Official TSE registration number (NR_PROTOCOLO_REGISTRO).
registration_date	date	YYYY-MM-DD	Date filed with the TSE (DT_REGISTRO).
own_poll	string	S | N	S = institute's own poll; N = commissioned by a third party (ST_PESQUISA_PROPRIA).
cnpj	string	14 digits	Polling company's CNPJ (NR_CNPJ_EMPRESA).
institute	string	—	Polling company, legal name (NM_EMPRESA).
institute_trade_name	string	—	Trade name, when declared (NM_EMPRESA_FANTASIA).
office	string	—	Office polled (DS_CARGO) — filtered to Presidente.
field_start / field_end	date	YYYY-MM-DD	Fieldwork window (DT_INICIO/FIM_PESQUISA).
publication_date	date	YYYY-MM-DD	Planned/actual publication date (DT_DIVULGACAO; may be future for registered-but-unreleased polls).
sample_size	integer	respondents	Declared sample size (QT_ENTREVISTADO).
conre	string	—	Regional Statistics Council registration of the responsible statistician (CD_CONRE).
statistician	string	—	Responsible statistician, named (NM_ESTATISTICO_RESP).
cost_brl	number	BRL	Declared cost of the poll (VR_PESQUISA).
methodology	string (long)	free text	Full methodology description (DS_METODOLOGIA_PESQUISA) — survey type, mode (in-person/phone), instrument. Up to ~3.8k chars; not truncated.
sampling_plan	string (long)	free text	Full sampling/weighting design (DS_PLANO_AMOSTRAL) — universe, multi-stage cluster design, and the demographic/geographic quota design (sex, age, education, income, region) with the exact quota percentages when declared. Up to ~4k chars; not truncated. This is the registration-level weighting design.
control_system	string (long)	free text	Internal field-control/quality-control system (DS_SISTEMA_CONTROLE).
municipality_data	string	free text	Municipality-level breakdown declaration (DS_DADO_MUNICIPIO), when present.
uf	string	2-letter UF or BR	Federative unit (SG_UF). Always BR for presidential-office registrations — the TSE files all presidential polls under the national jurisdiction regardless of where the sample was drawn (see scope).
electoral_unit	string	—	Electoral unit name (NM_UE) — BRASIL for all presidential registrations.
scope	string	national | state | unknown	AFOS-derived sample-coverage label (not a native TSE field). national = declared universe spans more than one UF / the country; state = restricted to a single UF (a single municipality is within one UF, so municipal polls are state); unknown = the registration text does not declare a universe (left honest, never guessed). See provenance note below.
scope_source	string	methodology | sampling_plan | dado_municipio | none	Which registration field the scope was inferred from — for auditability/reproducibility. none ⇔ scope = unknown.

⚠️ "Registered" ≠ "published". A poll in the registry has been filed with the TSE; it may be delayed or never released. Confirm actual release against a primary source before citing numbers.

🔎 What the TSE publishes vs not. Public (in this file): methodology, sampling/weighting design, cost, contracting party, named statistician, fieldwork dates, sample size. Not in the open-data file: the per-candidate results and their demographic crosstabs (published by the institute, not the TSE), and the complete questionnaire (art. 33 VI) — that is an attachment in the TSE PesqEle system, not in the open-data CSV.

🧭 scope is AFOS-inferred, not a TSE classification. The TSE does not label a poll's sample as national or state. It registers by the office polled: any poll asking about Presidente is filed under the national jurisdiction (SG_UF=BR, NM_UE=BRASIL) even when the sample covers a single state. The actual geographic reach lives only in the institute's free-text methodology / sampling plan / municipality declaration. scope is AFOS's transparent inference from that text: national when the declared universe spans more than one UF / the country (signals: "eleitorado brasileiro", "residente no Brasil", "todas as regiões do Brasil", "N unidades da federação", "todo o país", "âmbito nacional"); state when restricted to one UF (a municipality is within one UF → state); unknown when no universe is declared. scope_source records which field the decision came from. This is a documented derivation, not a field the TSE certifies — verify against the registration text (included in this file) for any rigorous use.

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polls/national-poll-results-firstround.csv

Published first-round results, long format (one row per candidate × scenario × poll).

Column	Type	Notes
poll_id	string	TSE register if available, else institute-date.
register_tse	string	TSE registration number (blank if unregistered/commissioned).
institute	string	Polling institute.
poll_date	date	Publication date (YYYY-MM-DD).
field_dates	string	Fieldwork window as published.
sample	integer	Sample size.
margin_pp	number	Margin of error, percentage points.
method	string	e.g. "Pesquisa nacional", "Telefônica".
scenario	string	Scenario label (some polls test multiple candidate sets).
candidate	string	Candidate name.
party	string	Party, parsed from the candidate label.
percent	number	Voting intention, %.

polls/national-poll-results-secondround.csv

Published runoff matchups.

Column	Type	Notes
poll_id, register_tse, institute, poll_date	—	As above.
matchup	string	e.g. "Lula vs Flávio".
candidate1 / percent1	string / number	First candidate and %.
candidate2 / percent2	string / number	Second candidate and %.

polls/national-polls.json

Full structured array of the 22 deduplicated national polls with results (first round + runoff scenarios + methodology + sources), reconstructed from the git history of the AFOS dashboard's polls-data.json. Deduplicated by TSE register (fallback: institute + date), keeping the most complete version of each poll.

Each poll carries a tse_registration object linking it to its public TSE registration (from tse-registry above):

Field	Notes
register_tse	Matched TSE protocol.
matched_by	protocol = exact protocol match (8/22); institute+date(±Nd) = nearest same-institute registration within N days (14/22). For institute+date matches the attached methodology/sampling design is the institute's standard (stable across waves), not a claim of identical protocol.
cnpj, institute_full, statistician, conre, cost_brl, own_poll	Registration metadata.
methodology, sampling_plan, control_system	Full registration text (see tse-registry schema). null when no confident match.

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data/market-odds-timeseries.csv

Polymarket presidential winner odds per candidate, daily.

Column	Type	Notes
date	date	YYYY-MM-DD.
candidate	string	First-name key (e.g. "Lula", "Flávio").
party	string	Party.
polymarket_pct	number	Implied probability, %.
volume_usd_m	number	Cumulative traded volume, USD millions. Blank for legacy snapshots (pre-2026-05-22) that did not record volume.

Extracted by regex from each daily analysis-criteriosa.json quadroComparativo[].m field — no value is fabricated; candidates without a parseable market price are omitted.

data/divergence-timeseries.csv

Market × poll divergence — the dataset's namesake signal. Each national-poll first-round result is joined to the candidate's Polymarket odds on the poll's date.

Column	Type	Notes
poll_date	date	Poll publication date.
institute	string	Polling institute.
register_tse	string	TSE register.
candidate	string	Canonical candidate key.
poll_pct	number	Poll voting intention, %.
polymarket_pct	number	Market implied probability on polymarket_date, %.
polymarket_date	date	Market date used: nearest available on or before poll_date.
divergence_pp	number	polymarket_pct − poll_pct, percentage points.

Interpretation caveat: a poll reports first-round vote share; a Polymarket contract prices probability of winning the election. The two are different quantities — divergence_pp measures the gap between the market's win-probability and the poll's vote share, which is the spread AFOS tracks editorially, not a like-for-like error metric. Candidate names are normalized across sources via an explicit mapping (see scripts/export-hf-dataset.mjs).

data/divergence-{date}.csv

Per-day snapshot: date, candidate, polymarket_pct, poll_pct, divergence_pp.

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snapshots/analysis-criteriosa/{date}.json

Daily structured analysis. Key fields: updatedAt, subtitle, cruzamento (the day's cross-source reading), candidates[] (per-candidate header/analise/fortes/fracos), and quadroComparativo[] — the comparison table where m = market price string, p = poll mentions, t = trend reading, s = sources.

snapshots/analysis-cards/{date}.json

Thematic cards: sentimento, inss, bancoMaster, stf (incl. impeachment market %).

news/news-{date}.json

{ date, count, items[] }, where each item is { source, title, url, published }. Links only — no article bodies.

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Research enrichment (2026-06-13) — poll-centric analytical layers

Three additions for methodological/research use. They add depth; nothing in the base files changed in meaning.

New fields on each poll in polls/national-polls.json

Field	Type	Notes
field_window	object/null	{ start, end } — fieldwork dates from the poll's TSE registration.
field_midpoint	date	Midpoint of the fieldwork window. A poll is best dated by its field midpoint, not its publication date.
dating_source	string	field_midpoint (all 22 current polls), publication_date (fallback), or unavailable.
days_to_first_round	int	Days from field_midpoint to the 1st round (2026-10-04). Positive = before election.
days_to_runoff	int	Days from field_midpoint to the runoff (2026-10-25).
tse_registration.sample_design	object	Sample composition/weighting (layer A) — see below.

tse_registration.sample_design — sample-design demographics (layer A)

Parsed from the TSE sampling_plan registration text. This is the declared composition/weighting of the SAMPLE (quota frame), NOT vote-by-demographic crosstabs (layer B). Layer B is not part of Brazil's TSE open data — institutes publish it separately — so it is intentionally absent here.

Field	Type	Notes
quota_detail_level	string	full_percentages (institute declared quotas with %; 12/22 polls), mentioned_no_pct (controls named, no % in registry; 10/22), or not_in_sampling_text.
control_variables	object	Booleans for sex, age, education, income, region — whether the design controls/weights on each.
sex_quota	object/null	{ male_pct, female_pct } where declared.
age_quota / education_quota / income_quota	array/null	[{ label, pct }] where declared (each declared dimension sums to ~100%).

Best-effort extraction from free text; null where the institute did not declare structured percentages. No value is fabricated.

polls/sample-demographics.csv

Flat (long) view of layer A: poll_id, register_tse, institute, poll_date, field_midpoint, dimension, category, pct, quota_detail_level. One row per declared (dimension, category). Polls that only name controls without % carry a single (declared, no % in registry) row per dimension — explicit coverage, not a hidden gap.

data/poll-divergence.csv

Poll-level market×poll pairing anchored on the field midpoint (vs the publication-date-anchored divergence-timeseries.csv).

Column	Type	Notes
poll_id, register_tse, institute, poll_date, field_midpoint, days_to_first_round, scenario, candidate	—	Poll/candidate identity.
poll_pct	number	First-round vote share, %.
polymarket_pct	number	Market implied win-probability on polymarket_date, %.
polymarket_date	date	Nearest market date on or before the field midpoint (no fabricated contemporaneity; polls predating the market series start, 2026-04-17, have no row).
naive_gap_pp	number	polymarket_pct − poll_pct, percentage points.
gap_type	string	Always naive_winprob_minus_voteshare — a flag, not a metric: the market prices P(win) while the poll reports vote share, so the gap is not scale-reconciled. Reconciling the scales (e.g. mapping vote share to a win probability) is a modeling choice left to the researcher.