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Tarefa crb_papers.q046

crb_papersagentT2publicépoca 1, tentativa 1Execução: 20261015T170957Z-suite-crb_papers-baseline-dae0c1

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, nenhuma estimativa citada.
no answer figure: the answer cites no effect of an estimator call

Pergunta feita ao analista

How did county presidential-election turnout change between 1992 and 1996 in counties that experienced a recorded Black church arson incident, compared with counties that did not experience such incidents during that period?

Resposta

Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.

Valores esperados e de onde vêm

crb_papers.q046.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 46 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['46'].effect and .standard_error
Trecho
index 46: effect 0.05766, standard_error 0.0077384
Valor como publicado
0.05765999455808379
Erro-padrão como publicado
0.007738399871299681
Valor
0,057660.05765999455808379 (se 0,00773840.007738399871299681)
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: 0,057660.05765999455808379 · relativa 0.000001 · absoluta 7.738399871299681e-9
  • #3 figura da resposta próxima: 0,00773840.007738399871299681 · relativa 0.000001 · absoluta 7.738399871299681e-9

crb_papers.q046.script

Fonte
CausalReasoningBenchmark reference estimation script for index 46
Tipo
software
Localização
solutions/research_papers/DiD/Marsh_2023/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 2310 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
17138ea46f05dc2d6c3c051afb3b8f54dac9323725a399e5e87988fe3da59497 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Marsh_2023/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
    no answer figure: the answer cites no effect of an estimator call
    obrigatóriafalhou[0.042492730810336415,0.07282725830583116]—interval · [0.042492730810336415, 0.07282725830583116]——
    2figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,057660.05765999455808379—relativa 0.000001 · absoluta 7.738399871299681e-9crb_papers.q046.gold—
    3figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,00773840.007738399871299681—relativa 0.000001 · absoluta 7.738399871299681e-9crb_papers.q046.gold—

    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.olsO agente não fez uma chamada de estimação que a resposta cite.

    Trajetória

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

    1. 0Início

      How did county presidential-election turnout change between 1992 and 1996 in counties that experienced a recorded Black church arson incident, compared with counties that did not experience such incidents during that period?

      ds_0024 (agent)

      | Variable Name | Description | | --- | --- | | turnout | County presidential-election turnout rate in the general election, measured as total ballots cast divided by the county voting-age population (unit interval 0–1). Votes and voting-age population were assembled from standard U.S. election and Census tabulations for each election year. | | tr_ar | Indicator (0/1) that at least one Black church arson incident was recorded in the county within the election-cycle window associated with that year. Incidents are drawn from the U.S. Department of Justice’s National Church Arson Task Force records (primarily 1995–2000) and mapped to the relevant presidential-election cycle for comparability across counties and years. | | perc_bl | Share of county residents identifying as Black or African American in that year (0–1), based on U.S. Census/ACS population statistics for the county. | | pop_tot | Total county population (persons) in that year, from U.S. Census/ACS population counts. | | income | County median household income in U.S. dollars for that year (nominal dollars as reported by the Census/ACS). | | fips | Five-digit Federal Information Processing Standards (FIPS) code uniquely identifying the county (state–county concatenated code). | | year | Presidential election year for the observation (e.g., 1980, 1984, …, 2016). | Dataset Context: This file is a county-by–presidential-election-year panel covering U.S. general elections from 1980 through 2016. Each record is keyed by a county’s five-digit FIPS code and the presidential election year. Turnout is constructed from county-level counts of ballots cast in the presidential general election combined with county voting-age population from the U.S. Census Bureau. Using voting-age population standardizes the denominator across states, which vary in registration rules and reporting conventions, but note that VAP includes individuals ineligible to vote (e.g., noncitizens), a common feature of administrative turnout measures. Demographic indicators—total population, the share identifying as Black or African American, and median household income—are taken from decennial Census and American Community Survey tabulations aligned to the election year. Income is recorded in nominal dollars for the reported year. The Black church arson indicator comes from administrative records compiled by the U.S. Department of Justice’s National Church Arson Task Force established in the mid-1990s. Those incident locations are assigned to counties and linked to the presidential-election cycle that encompasses the incident window to ensure a consistent temporal frame across units. Because the Task Force’s comprehensive catalog primarily spans 1995–2000, county-years outside that period are generally coded as having no recorded incident. Users should be aware that counties occasionally experience boundary changes or renamings over long panels; the dataset relies on FIPS coding to maintain consistent identification. As with most historical administrative compilations, reporting conventions can vary across states and years; the assembly here harmonizes these inputs to produce a cohesive, national county-level panel suitable for studying election-period patterns alongside population and community characteristics.

      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      ref_evp (reference)
      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      1. select {"columns":["turnout","tr_ar","perc_bl","pop_tot","income","fips","year"]}
      2. dropna {"columns":["turnout","tr_ar","fips","year"]}
      3. filter {"query":"year <= 1996"}
      4. collapse {"aggs":[{"column":"tr_ar","fn":"max","name":"evp"}],"by":["fips"]}
      ref_panel (reference)
      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      1. select {"columns":["turnout","tr_ar","perc_bl","pop_tot","income","fips","year"]}
      2. dropna {"columns":["turnout","tr_ar","fips","year"]}
      3. filter {"query":"year in [1992, 1996]"}
      4. merge {"how":"left","on":["fips"],"with":"ref_years"}
      5. filter {"query":"nyears == 2"}
      6. merge {"how":"inner","on":["fips"],"with":"ref_pre"}
      7. merge {"how":"inner","on":["fips"],"with":"ref_post"}
      8. merge {"how":"left","on":["fips"],"with":"ref_evp"}
      9. filter {"query":"tr_pre == 0 and (tr_post == 1 or (tr_post == 0 and evp == 0))"}
      10. derive {"args":{"cmp":"eq","column":"tr_post","value":1},"name":"treated_group","op":"indicator"}
      11. derive {"args":{"cmp":"eq","column":"year","value":1996},"name":"post","op":"indicator"}
      12. derive {"args":{"columns":["post","perc_bl_pre"]},"name":"post_x_perc_bl_pre","op":"product"}
      13. derive {"args":{"columns":["post","pop_tot_pre"]},"name":"post_x_pop_tot_pre","op":"product"}
      14. derive {"args":{"columns":["post","income_pre"]},"name":"post_x_income_pre","op":"product"}
      15. derive {"args":{"columns":["treated_group","post"]},"name":"did","op":"interaction"}
      ref_post (reference)
      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      1. select {"columns":["turnout","tr_ar","perc_bl","pop_tot","income","fips","year"]}
      2. dropna {"columns":["turnout","tr_ar","fips","year"]}
      3. filter {"query":"year == 1996"}
      4. select {"columns":["fips","tr_ar"]}
      5. rename {"map":{"tr_ar":"tr_post"}}
      ref_pre (reference)
      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      1. select {"columns":["turnout","tr_ar","perc_bl","pop_tot","income","fips","year"]}
      2. dropna {"columns":["turnout","tr_ar","fips","year"]}
      3. filter {"query":"year == 1992"}
      4. select {"columns":["fips","tr_ar","perc_bl","pop_tot","income"]}
      5. rename {"map":{"income":"income_pre","perc_bl":"perc_bl_pre","pop_tot":"pop_tot_pre","tr_ar":"tr_pre"}}
      ref_years (reference)
      file d73be27ea1d43f15d8e48b09dfc8299de15152438ea0d0b908fcad88c89b3c43 · frame —
      1. select {"columns":["turnout","tr_ar","perc_bl","pop_tot","income","fips","year"]}
      2. dropna {"columns":["turnout","tr_ar","fips","year"]}
      3. filter {"query":"year in [1992, 1996]"}
      4. collapse {"aggs":[{"column":"turnout","fn":"count","name":"n"}],"by":["fips","year"]}
      5. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["fips"]}
    2. 1Turno do modelo
      call_b8d76c9brules-1Fim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
      Chamadas pedidas
      • submit_answer (meta-ferramenta)
        {
          "answer": "Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.",
          "caveats": [],
          "figure_refs": []
        }
    3. 2Guarda
      resposta aceita
      Números encontrados
      —
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    4. 3Resposta

      Pelas regras deste roteador não identifiquei um desenho que responda à pergunta; nenhuma estimativa foi feita.

      Figuras citadas: — · Parada: answered
    5. 4Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    6. 5Pontuação
      #1figura da resposta próximafalhouobrigatóriano answer figure: the answer cites no effect of an estimator call
    7. 6Pontuação
      #2figura da resposta próximafalhouregistradano answer figure: the answer cites no effect of an estimator call
    8. 7Pontuação
      #3figura da resposta próximafalhouregistradano answer figure: the answer cites no effect of an estimator call

    Épocas × verificações

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

    Tentativas

    Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.

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