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Tarefa crb_papers.q039

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

Among cities with observed reform status at both censuses, how did adopting a civil service commission after 1930 and by 1940 affect the change from 1930 to 1940 in the share of blue-collar city jobs held by foreign-born white residents, compared with cities that had not adopted by 1940, adjusting for the city's foreign-born white population share?

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.q039.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 39 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['39'].effect and .standard_error
Trecho
index 39: effect 0.0141794, standard_error 0.0311452
Valor como publicado
0.014179411903156684
Erro-padrão como publicado
0.031145196886261866
Valor
0,01417940.014179411903156684 (se 0,03114520.031145196886261866)
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: 0,01417940.014179411903156684 · relativa 0.000001 · absoluta 3.1145196886261864e-8
  • #3 figura da resposta próxima: 0,03114520.031145196886261866 · relativa 0.000001 · absoluta 3.1145196886261864e-8

crb_papers.q039.script

Fonte
CausalReasoningBenchmark reference estimation script for index 39
Tipo
software
Localização
solutions/research_papers/DiD/Kuipers_Sahn_2023/question_2/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 1872 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
c8d4df2eb63f706756a413d7712f493121c7b4b498e33cdd5c159a4acd12c6e7 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Kuipers_Sahn_2023/question_2/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[-0.04686517399391657,0.07522399780022994]—interval · [-0.04686517399391657, 0.07522399780022994]——
    2figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,01417940.014179411903156684—relativa 0.000001 · absoluta 3.1145196886261864e-8crb_papers.q039.gold—
    3figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,03114520.031145196886261866—relativa 0.000001 · absoluta 3.1145196886261864e-8crb_papers.q039.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

      Among cities with observed reform status at both censuses, how did adopting a civil service commission after 1930 and by 1940 affect the change from 1930 to 1940 in the share of blue-collar city jobs held by foreign-born white residents, compared with cities that had not adopted by 1940, adjusting for the city's foreign-born white population share?

      ds_0020 (agent)

      | Variable Name | Description | | --- | --- | | treat | Binary indicator equal to 1 if the municipality had established a municipal civil service commission (merit-based personnel system) by the given census year; 0 if not yet established. Values are weakly increasing over time within a city. Sourced primarily from U.S. Civil Service Assembly municipal surveys (1937, 1940, 1943) and corroborated by state statutes; may be missing (blank/NA) where adoption year could not be determined. | | pop_prop | Proportion (0–1) of the city’s residents who are foreign-born whites in that census year. Constructed from full-count decennial U.S. Census microdata using birthplace (foreign-born) and enumerated race (white). Available for decennial years 1850–1940 except 1890 (destroyed census). | | govt_prop | Proportion (0–1) of blue-collar municipal government employees who are foreign-born whites in that census year. Computed from full-count decennial U.S. Census microdata by identifying residents employed in local public administration and classifying blue-collar occupations (e.g., craftsmen, mechanics, service workers, laborers); police and fire personnel are excluded due to distinct recruitment regimes. Counts reflect resident workers and assume city employment generally coincides with residence in this era. | | city | Municipality name and two-letter state abbreviation in the standardized format “city, st” (e.g., “aberdeen, sd”). Standardization facilitates consistent tracking across sources and decades; cities with the same name are distinguished by state. | | YEAR | Decennial census year for which measures are calculated (integers from 1850 to 1940; 1890 absent due to the lost census). | Dataset Context: This dataset follows U.S. municipalities at ten-year intervals from the mid-19th to early-20th centuries, a period spanning patronage-based municipal staffing through the widespread diffusion of merit-oriented civil service systems. Municipal adoption of civil service rules was recorded by the U.S. Civil Service Assembly in nationwide surveys conducted in 1937, 1940, and 1943 and supplemented by state-level statutes that, in many cases, mandated adoption using population thresholds. The “treat” indicator reflects whether a city had a functioning municipal civil service commission by a given census year; because commissions, once established, typically persisted, the indicator does not toggle back to zero for later years. Demographic and employment composition measures are derived from the full-count decennial U.S. Censuses (1850–1940, with 1890 unavailable). The census enumerated every resident and captured birthplace, race, industry, and occupation, allowing identification of local public administration workers and classification of blue-collar positions. Blue-collar categories include craftsmen, mechanics, service workers, and laborers; police and fire employees are excluded because their hiring, promotion, and protection rules often followed distinct legal frameworks. Because the census does not name employers, municipal employment is inferred from the industry code “local public administration,” and, consistent with transportation realities of the era, employees are assumed to work in the municipality where they reside. The civil service systems cataloged here typically introduced commission oversight of hiring, promotion, and termination in “classified” services, commonly relying on publicly advertised examinations and shortlists (e.g., a “rule of three”). “Unclassified” roles (e.g., department heads, certain temporary staff) fell outside commission rules, and the scope of coverage varied across cities and over time. City names are standardized to “city, st” to harmonize historical references across sources and decades. Shares are expressed as proportions between 0 and 1 and are calculated at the city–year level to align with the decennial timing of the underlying census enumerations.

      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      ref_fty (reference)
      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      1. select {"columns":["city","YEAR","treat","govt_prop","pop_prop"]}
      2. rename {"map":{"YEAR":"year"}}
      3. dropna {"columns":["city","year","treat","govt_prop","pop_prop"]}
      4. filter {"query":"treat == 1"}
      5. collapse {"aggs":[{"column":"year","fn":"min","name":"fty"}],"by":["city"]}
      ref_panel (reference)
      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      1. select {"columns":["city","YEAR","treat","govt_prop","pop_prop"]}
      2. rename {"map":{"YEAR":"year"}}
      3. dropna {"columns":["city","year","treat","govt_prop","pop_prop"]}
      4. filter {"query":"year in [1930, 1940]"}
      5. merge {"how":"left","on":["city"],"with":"ref_years"}
      6. filter {"query":"nyears == 2"}
      7. merge {"how":"inner","on":["city"],"with":"ref_pre"}
      8. merge {"how":"inner","on":["city"],"with":"ref_post"}
      9. merge {"how":"left","on":["city"],"with":"ref_fty"}
      10. filter {"query":"t_pre == 0 and (t_post == 1 or (t_post == 0 and (fty != fty or fty > 1940)))"}
      11. derive {"args":{"cmp":"eq","column":"t_post","value":1},"name":"Treated","op":"indicator"}
      12. derive {"args":{"cmp":"eq","column":"year","value":1940},"name":"Post","op":"indicator"}
      13. derive {"args":{"columns":["Treated","Post"]},"name":"Treated_Post","op":"interaction"}
      ref_post (reference)
      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      1. select {"columns":["city","YEAR","treat","govt_prop","pop_prop"]}
      2. rename {"map":{"YEAR":"year"}}
      3. dropna {"columns":["city","year","treat","govt_prop","pop_prop"]}
      4. filter {"query":"year == 1940"}
      5. collapse {"aggs":[{"column":"treat","fn":"max","name":"t_post"}],"by":["city"]}
      ref_pre (reference)
      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      1. select {"columns":["city","YEAR","treat","govt_prop","pop_prop"]}
      2. rename {"map":{"YEAR":"year"}}
      3. dropna {"columns":["city","year","treat","govt_prop","pop_prop"]}
      4. filter {"query":"year == 1930"}
      5. collapse {"aggs":[{"column":"treat","fn":"max","name":"t_pre"}],"by":["city"]}
      ref_years (reference)
      file fb21d9bfd9e8815223675810e217e1db86e4bbf0d90e6a351772c71a5d17b441 · frame —
      1. select {"columns":["city","YEAR","treat","govt_prop","pop_prop"]}
      2. rename {"map":{"YEAR":"year"}}
      3. dropna {"columns":["city","year","treat","govt_prop","pop_prop"]}
      4. filter {"query":"year in [1930, 1940]"}
      5. collapse {"aggs":[{"column":"treat","fn":"count","name":"n"}],"by":["city","year"]}
      6. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["city"]}
    2. 1Turno do modelo
      call_0ef3186erules-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

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