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Tarefa crb_papers.q024

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

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
0.0681838023 in [0.09657938754, 0.2820310219]?

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

Pergunta feita ao analista

By how many percentage points did adopting same-day voter registration in 1994 alter a state's CPS-based voter turnout between the prior and subsequent election?

Resposta

Estimativa ingênua (infer.ols): coef.temp_var = 0,06818.

Valores esperados e de onde vêm

crb_papers.q024.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 24 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['24'].effect and .standard_error
Trecho
index 24: effect 0.189305, standard_error 0.0473091
Valor como publicado
0.18930520472316303
Erro-padrão como publicado
0.04730909039725135
Valor
0,1893050.18930520472316303 (se 0,04730910.04730909039725135)
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: 0,1893050.18930520472316303 · relativa 0.000001 · absoluta 4.7309090397251344e-8
  • #3 figura da resposta próxima: 0,04730910.04730909039725135 · relativa 0.000001 · absoluta 4.7309090397251344e-8

crb_papers.q024.script

Fonte
CausalReasoningBenchmark reference estimation script for index 24
Tipo
software
Localização
solutions/research_papers/DiD/Grumbach_Hill/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 1203 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
d7a924545bbe5138d889896ae270bb799e5491780bcab8836ce0668df6e9e26e (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Grumbach_Hill/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
    0.0681838023 in [0.09657938754, 0.2820310219]?
    obrigatóriafalhou[0.0965793875445504,0.28203102190177565]0,06818380.06818380229518727interval · [0.0965793875445504, 0.28203102190177565]—call_a57a5116
    2figura da resposta próxima
    0.0681838023 vs 0.18930520472316303
    registradafalhou0,1893050.189305204723163030,06818380.06818380229518727relativa 0.000001 · absoluta 4.7309090397251344e-8crb_papers.q024.goldcall_a57a5116
    3figura da resposta próxima
    0.01250342931 vs 0.04730909039725135
    registradafalhou0,04730910.047309090397251350,01250340.012503429308683423relativa 0.000001 · absoluta 4.7309090397251344e-8crb_papers.q024.goldcall_a57a5116

    Caminho de referência e caminho do agente

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

    caminho de referência do item · benchmark_script

    Referência: infer.olsChamada do agente: infer.ols (call_a57a5116)igual
    Argumentos da referência e do agente
    ArgumentoReferênciaAgente
    cluster"state"—diferente
    controls["treated","post"][]diferente
    dataset"ref_panel""ds_0013"diferente
    fe—[]não fixado pela referência
    intercept—truenão fixado pela referência
    level—0,950.95não fixado pela referência
    se—"HC1"não fixado pela referência
    subset——não fixado pela referência
    weights——não fixado pela referência
    x["treated_post"]["temp_var"]diferente
    y"voted""voted"igual

    Trajetória

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

    1. 0Início

      By how many percentage points did adopting same-day voter registration in 1994 alter a state's CPS-based voter turnout between the prior and subsequent election?

      ds_0013 (agent)

      | Variable Name | Description | | --- | --- | | voted | State-year turnout rate (0–1), aggregated from the Census Bureau’s Current Population Survey Voting and Registration Supplement. Computed as the share of adult residents surveyed in that state and year who report having voted in the November general election. Includes both presidential and midterm cycles and reflects CPS’s biennial November fielding and weighting. | | temp_var | Indicator (0/1) that residents could register and cast a ballot on the same day in that state and year. Status reflects the first general election in which the option was implemented, and remains 1 thereafter. Codings draw on legislative and administrative sources and treat Election Day registration as part of the same “same-day” category. | | state | U.S. state name corresponding to each panel unit. | | year | Calendar election year (even-numbered), matching the CPS Voter Supplement cycle and covering both presidential and midterm general elections. | Dataset Context: This file is a state-by-year panel spanning 1980–2018 that aligns survey-based measures of participation with the timing of state registration rules. Turnout is derived from the Census Bureau’s Current Population Survey (CPS) Voting and Registration Supplement, a large, nationally representative survey of the civilian, noninstitutionalized population conducted every two years in November. The CPS asks respondents whether they voted in the most recent general election and provides sampling weights to recover population-representative estimates. Aggregating these responses to the state-year level yields a consistent series of turnout rates across both presidential and midterm elections. As with any self-reported voting measure, the CPS can modestly overstate participation, but it is widely used for its coverage, consistent questionnaire, and long time span. Policy status for same-day registration is compiled from legislative and administrative references, including nonpartisan compilations and state records, and is coded to reflect the first election in which residents could register and vote on the same day. Jurisdictions that permit registration on Election Day itself are included under the same umbrella as those allowing same-day registration during an early voting window. Once a state implements the option, its indicator remains active in subsequent even-year elections unless the policy is rescinded. By harmonizing CPS-based turnout with the timing of registration options, the dataset supports comparisons of participation patterns across places and over time. The panel includes both high-salience presidential contests and midterm cycles, allowing researchers to examine differences that can arise across election types while working with a uniform measurement framework.

      file 5b884bcf1e4ee621cad50fd984e81c33cf38702b12ff606d79bfa868f56d9acb · frame —
      ref_panel (reference)
      file 5b884bcf1e4ee621cad50fd984e81c33cf38702b12ff606d79bfa868f56d9acb · frame —
      1. select {"columns":["voted","temp_var","state","year"]}
      2. dropna {"columns":["voted","temp_var","state","year"]}
      3. filter {"query":"year in [1992, 1994]"}
      4. merge {"how":"left","on":["state"],"with":"ref_years"}
      5. filter {"query":"nyears == 2"}
      6. merge {"how":"inner","on":["state"],"with":"ref_pre"}
      7. merge {"how":"inner","on":["state"],"with":"ref_post"}
      8. filter {"query":"t_pre == 0 and (t_post == 1 or t_post == 0)"}
      9. derive {"args":{"cmp":"eq","column":"t_post","value":1},"name":"treated","op":"indicator"}
      10. derive {"args":{"cmp":"eq","column":"year","value":1994},"name":"post","op":"indicator"}
      11. derive {"args":{"columns":["treated","post"]},"name":"treated_post","op":"interaction"}
      ref_post (reference)
      file 5b884bcf1e4ee621cad50fd984e81c33cf38702b12ff606d79bfa868f56d9acb · frame —
      1. select {"columns":["voted","temp_var","state","year"]}
      2. dropna {"columns":["voted","temp_var","state","year"]}
      3. filter {"query":"year == 1994"}
      4. collapse {"aggs":[{"column":"temp_var","fn":"max","name":"t_post"}],"by":["state"]}
      ref_pre (reference)
      file 5b884bcf1e4ee621cad50fd984e81c33cf38702b12ff606d79bfa868f56d9acb · frame —
      1. select {"columns":["voted","temp_var","state","year"]}
      2. dropna {"columns":["voted","temp_var","state","year"]}
      3. filter {"query":"year == 1992"}
      4. collapse {"aggs":[{"column":"temp_var","fn":"max","name":"t_pre"}],"by":["state"]}
      ref_years (reference)
      file 5b884bcf1e4ee621cad50fd984e81c33cf38702b12ff606d79bfa868f56d9acb · frame —
      1. select {"columns":["voted","temp_var","state","year"]}
      2. dropna {"columns":["voted","temp_var","state","year"]}
      3. filter {"query":"year in [1992, 1994]"}
      4. collapse {"aggs":[{"column":"voted","fn":"count","name":"n"}],"by":["state","year"]}
      5. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["state"]}
    2. 1Turno do modelo
      call_2da6519dnaive-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_0013",
          "x": [
            "temp_var"
          ],
          "y": "voted"
        }
    3. 2Ferramenta
      infer.olsv0.1.0call_a57a5116decidido pelo modeloreexecutável

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

      Argumentos
      {
        "cluster": null,
        "controls": [],
        "dataset": "ds_0013",
        "fe": [],
        "intercept": true,
        "level": 0.95,
        "se": "HC1",
        "subset": null,
        "weights": null,
        "x": [
          "temp_var"
        ],
        "y": "voted"
      }
      Figuras call_a57a5116
      ChaveValorValor brutoErro-padrãoIC
      coef.temp_var
      Coefficient on temp_var in the regression of voted
      0,0681838 0.068183802295187270,01250340.0125034293086834230,0436472 – 0,0927204
      Diagnósticos
      • n_obs = 980980
      • k = 22
      • r2 = 0,03599980.03599979646797158
      • df_resid = 978978
      • se_type = "HC1"
      • n_clusters = —
      Tabelas (1)
      {
        "coefficients": [
          {
            "ci_high": 0.31614068378184607,
            "ci_low": 0.2997904191642978,
            "coef": 0.3079655514730719,
            "p": 0,
            "se": 0.0041659005540643475,
            "t": 73.9253247830445,
            "term": "Intercept"
          },
          {
            "ci_high": 0.09272043911244535,
            "ci_low": 0.043647165477929184,
            "coef": 0.06818380229518727,
            "p": 6.265831878856374e-8,
            "se": 0.012503429308683423,
            "t": 5.453208124896964,
            "term": "temp_var"
          }
        ]
      }
      Digests dos dados
      ds_0013 9b5a550f37a1fdaed15fefa260950e8b6ec3e25fd303fc640d93ad9f5ca9bf02
      sha256 do resultado
      66dd55d54a2fbfbc8ab309c5759629a15989f0a73df8219e18c4e4d6499edd81
    4. 3Turno do modelo
      call_5168cdeanaive-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.temp_var = 0,06818.",
          "caveats": [],
          "figure_refs": [
            "call_a57a5116:coef.temp_var"
          ]
        }
    5. 4Guarda
      resposta aceita
      Números encontrados
      0,06818
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    6. 5Resposta

      Estimativa ingênua (infer.ols): coef.temp_var = 0,06818.

      Figuras citadas: call_a57a5116:coef.temp_var · Parada: answered
      Figura da resposta: call_a57a5116:coef.temp_var = 0,06818380.06818380229518727 (se 0,01250340.012503429308683423)
    7. 6Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    8. 7Pontuação
      #1figura da resposta próximafalhouobrigatória0.0681838023 in [0.09657938754, 0.2820310219]?
    9. 8Pontuação
      #2figura da resposta próximafalhouregistrada0.0681838023 vs 0.18930520472316303
    10. 9Pontuação
      #3figura da resposta próximafalhouregistrada0.01250342931 vs 0.04730909039725135

    Épocas × verificações

    Resultado de cada verificação em cada época pontuada
    #0123
    Época 1passoufalhoufalhoufalhou

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