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Tarefa crb_papers.q113

crb_papersagentT2publicépoca 1, tentativa 1Execução: 20261015T171027Z-suite-crb_papers-naive-54c3f2

Veredito

passouPassou em todas as verificações obrigatórias.

Família do método (das chamadas de ferramentas): ols (regression)

Pergunta feita ao analista

Among non-term-limited candidates in Brazil's closely contested 2008 mayoral elections who also ran in 2012, how did winning in 2008 affect the probability of running under a different party in 2012?

Resposta

Estimativa ingênua (infer.ols): coef.treat = -0,1742.

Valores esperados e de onde vêm

crb_papers.q113.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 113 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['113'].effect and .standard_error
Trecho
index 113: effect -0.156051, standard_error 0.0383762
Valor como publicado
-0.15605068407099687
Erro-padrão como publicado
0.038376195809532575
Valor
-0,156051-0.15605068407099687 (se 0,03837620.038376195809532575)
Conferido por
arquivo do benchmark · Read from the catalog at the pinned revision by scripts/freeze_crb_papers.py; the catalog states the value its estimation script prints.
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/causal_queries.json
Licença
MIT
  • #2 figura da resposta próxima: -0,156051-0.15605068407099687 · relativa 0.000001 · absoluta 3.8376195809532574e-8
  • #3 figura da resposta próxima: 0,03837620.038376195809532575 · relativa 0.000001 · absoluta 3.8376195809532574e-8

crb_papers.q113.script

Fonte
CausalReasoningBenchmark reference estimation script for index 113
Tipo
software
Localização
solutions/research_papers/RDD/novaes_2018/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 1704 bytes at the pinned revision; the reference path of the item is a transcription of this script into typed transforms and tool calls (never executed here).
Implementação
independente da ferramenta
sha256 da cópia lida
3e4f395e90921f05458ab2186c3cc624620fd7cece0ae6138fa18e7e6e4f5b20 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/RDD/novaes_2018/question_1/estimation.py
Licença
MIT

    Verificações

    Cada verificação, o que esperava, o que observou e a chamada que leu
    #VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
    0resposta com lastro
    every number backed
    obrigatóriapassou—[]———
    1figura da resposta próxima
    -0.1741906854 in [-0.2312680279, -0.08083334028]?
    obrigatóriapassou[-0.23126802785768072,-0.08083334028431302]-0,174191-0.17419068541300528interval · [-0.23126802785768072, -0.08083334028431302]—call_b09729b8
    2figura da resposta próxima
    -0.1741906854 vs -0.15605068407099687
    registradafalhou-0,156051-0.15605068407099687-0,174191-0.17419068541300528relativa 0.000001 · absoluta 3.8376195809532574e-8crb_papers.q113.goldcall_b09729b8
    3figura da resposta próxima
    0.0131968891 vs 0.038376195809532575
    registradafalhou0,03837620.0383761958095325750,01319690.013196889097503314relativa 0.000001 · absoluta 3.8376195809532574e-8crb_papers.q113.goldcall_b09729b8

    Caminho de referência e caminho do agente

    A chamada de referência ao lado da chamada que deu a resposta, argumento por argumento.

    Nenhum caminho de referência registrado para esta tarefa.

    Trajetória

    Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.

    1. 0Início

      Among non-term-limited candidates in Brazil's closely contested 2008 mayoral elections who also ran in 2012, how did winning in 2008 affect the probability of running under a different party in 2012?

      ds_0078 (agent)

      | Variable Name | Description | |-------------------|-------------------------------------------------------------------------------------------------| | Unnamed: 0 | Row index carried over from the original export. | | muni_code | Municipality identifier assigned by Brazil's electoral authority (TSE). | | year | Baseline mayoral election year; 2008 for every row in this extract. | | party | Party abbreviation of the focal mayoral candidate in the 2008 election. | | mun_place | Candidate's finishing position in the 2008 mayoral election: 1=winner, 2=runner-up. | | gov_party | Party abbreviation of the state governor for the municipality’s state in that cycle. | | gov_pct | Party’s vote share in the gubernatorial election within the municipality (proportion). | | de_pct | Party’s vote share for state deputy (deputado estadual) within the municipality (proportion). | | change | Candidate ran under a different party in 2012 than in 2008: 1=different party, 0=same party. The exact date of a party change is not recorded. | | attrition | Candidate did not appear in the 2012 mayoral election (1/0); always 0 in this repeat-candidate extract. | | margin | Candidate's 2008 mayoral vote margin relative to the win-loss threshold, in proportions; positive for winners and negative for runners-up. | | p_df_pct | Party’s vote share for federal deputy (deputado federal) in the previous cycle, municipality-level (proportion). | | df_pct | Party’s vote share for federal deputy (deputado federal) in the current cycle, municipality-level (proportion). | | treat | Candidate won the 2008 mayoral election: 1=winner, 0=runner-up. | | ineligible | Candidate was term-limited/ineligible to run in the next mayoral election (1/0); always 0 in this extract. | | p_de_pct | Party’s vote share for state deputy in the previous cycle, municipality-level (proportion). | | p_gov_pct | Party’s vote share for governor in the previous cycle, municipality-level (proportion). | | p_mun_pct | Party’s vote share for mayor in the previous municipal election (proportion). | | partyIncumbent | Indicator that the party held the mayor’s office prior to the municipal election (1/0). | | age | Age of the focal mayoral candidate (years). | | max_expenditure | Reported maximum campaign expenditure for the mayoral candidate (local currency; -1 indicates missing). | | married | Candidate reported marital status: married (1/0). | | unschooled | Candidate reported no formal schooling (1/0). | | tertiary | Candidate reported tertiary (college/university) education completed (1/0). | | female | Candidate sex: female (1/0). | | pt | Indicator that the candidate’s party is PT (1/0). | | pmdb | Indicator that the candidate’s party is PMDB (1/0). | | psdb | Indicator that the candidate’s party is PSDB (1/0). | | pr | Indicator that the candidate’s party is PR (1/0). | | pfl | Indicator that the candidate’s party is PFL/DEM (legacy label) (1/0). | | ptb | Indicator that the candidate’s party is PTB (1/0). | | pps | Indicator that the candidate’s party is PPS (1/0). | | pp | Indicator that the candidate’s party is PP (1/0). | | pdt | Indicator that the candidate’s party is PDT (1/0). | | psb | Indicator that the candidate’s party is PSB (1/0). | | bizz | Candidate occupation: businessperson/entrepreneur (1/0). | | rural_worker | Candidate occupation: rural worker (1/0). | | retiree | Candidate occupation: retiree/pensioner (1/0). | | trader | Candidate occupation: trader/merchant (1/0). | | public_employee | Candidate occupation: public employee/civil servant (1/0). | | teacher | Candidate occupation: teacher (1/0). | Data Description: Each row represents a first- or second-place candidate in Brazil's 2008 municipal mayoral elections. This extract contains 4,276 candidates who were not term-limited and who also appeared as mayoral candidates in 2012; year=2008, ineligible=0, and attrition=0 throughout. Comparing the candidate's party labels in the 2008 and 2012 elections establishes whether they ran under a different party in 2012. The outcome change is a binary party-switching indicator; its mean is a probability on a 0-1 scale. Candidates absent from the 2012 election are excluded, so the question concerns the observed repeat-candidate sample. This selection must be considered when interpreting a causal effect or generalizing beyond that sample. The data were compiled from election results and candidate-registration records maintained by Brazil's Tribunal Superior Eleitoral (TSE). Municipality identifiers are TSE codes. The file links candidate party affiliations across the two mayoral elections and includes 2008 election placement, vote margins, win indicators, demographics, and occupations. Municipality-level party vote shares for governor, federal deputy (deputado federal), and state deputy (deputado estadual), together with their lagged values, provide additional electoral context; they are separate from the party-switching outcome change. Party labels follow official abbreviations in use during the period, including legacy acronyms.

      file aadd89d16bdebe209aec58b6b95cbf00e3f12efe912d4f83cd2383d63d8866ad · frame —
    2. 1Turno do modelo
      call_b077656enaive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
      Texto visível

      Linha de base ingênua: regressão do resultado no tratamento, sem controles.

      Chamadas pedidas
      • infer.ols
        {
          "dataset": "ds_0078",
          "x": [
            "treat"
          ],
          "y": "change"
        }
    3. 2Ferramenta
      infer.olsv0.1.0call_b09729b8decidido pelo modeloreexecutável

      Motivo: Linha de base ingênua: regressão do resultado no tratamento, sem controles.

      Argumentos
      {
        "cluster": null,
        "controls": [],
        "dataset": "ds_0078",
        "fe": [],
        "intercept": true,
        "level": 0.95,
        "se": "HC1",
        "subset": null,
        "weights": null,
        "x": [
          "treat"
        ],
        "y": "change"
      }
      Figuras call_b09729b8
      ChaveValorValor brutoErro-padrãoIC
      coef.treat
      Coefficient on treat in the regression of change
      -0,174191 -0.174190685413005280,01319690.013196889097503314-0,200063 – -0,148318
      Diagnósticos
      • n_obs = 4.2764276
      • k = 22
      • r2 = 0,03812940.03812936220586616
      • df_resid = 4.2744274
      • se_type = "HC1"
      • n_clusters = —
      Tabelas (1)
      {
        "coefficients": [
          {
            "ci_high": 0.373343220308744,
            "ci_low": 0.3340381505172665,
            "coef": 0.35369068541300525,
            "p": 1.4303106765182105e-239,
            "se": 0.010024148212571275,
            "t": 35.28386431571733,
            "term": "Intercept"
          },
          {
            "ci_high": -0.1483179311396173,
            "ci_low": -0.20006343968639326,
            "coef": -0.17419068541300528,
            "p": 5.083719634125283e-39,
            "se": 0.013196889097503314,
            "t": -13.199374801593201,
            "term": "treat"
          }
        ]
      }
      Digests dos dados
      ds_0078 1252dbe18c01bda81be7cbcfeeb6fbc12fa1110d486d96a3b6f0a0f19602d6f3
      sha256 do resultado
      05445707726aa7bbfce4e07b21a3fc5038d09ac852b5e1881e9bbf931df11345
    4. 3Turno do modelo
      call_8039283anaive-olsFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
      Chamadas pedidas
      • submit_answer (meta-ferramenta)
        {
          "answer": "Estimativa ingênua (infer.ols): coef.treat = -0,1742.",
          "caveats": [],
          "figure_refs": [
            "call_b09729b8:coef.treat"
          ]
        }
    5. 4Guarda
      resposta aceita
      Números encontrados
      -0,1742
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    6. 5Resposta

      Estimativa ingênua (infer.ols): coef.treat = -0,1742.

      Figuras citadas: call_b09729b8:coef.treat · Parada: answered
      Figura da resposta: call_b09729b8:coef.treat = -0,174191-0.17419068541300528 (se 0,01319690.013196889097503314)
    7. 6Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    8. 7Pontuação
      #1figura da resposta próximapassouobrigatória-0.1741906854 in [-0.2312680279, -0.08083334028]?
    9. 8Pontuação
      #2figura da resposta próximafalhouregistrada-0.1741906854 vs -0.15605068407099687
    10. 9Pontuação
      #3figura da resposta próximafalhouregistrada0.0131968891 vs 0.038376195809532575

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