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Tarefa crb_papers.q029

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

For municipalities that first moved to council-based naturalization decisions in 2006 or 2009, how much did ordinary naturalization rates change from 1991 to 2009 relative to municipalities that never changed their local decision regime?

Resposta

Estimativa ingênua (infer.ols): coef.indirect = 1,108.

Valores esperados e de onde vêm

crb_papers.q029.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 29 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['29'].effect and .standard_error
Trecho
index 29: effect 0.815272, standard_error 0.463921
Valor como publicado
0.8152716551072032
Erro-padrão como publicado
0.46392069651186174
Valor
0,8152720.8152716551072032 (se 0,4639210.46392069651186174)
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: 0,8152720.8152716551072032 · relativa 0.000001 · absoluta 4.639206965118617e-7
  • #3 figura da resposta próxima: 0,4639210.46392069651186174 · relativa 0.000001 · absoluta 4.639206965118617e-7

crb_papers.q029.script

Fonte
CausalReasoningBenchmark reference estimation script for index 29
Tipo
software
Localização
solutions/research_papers/DiD/Hainmueller_Hangartner_2019/question_2/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 2682 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
955cfba911624072407f79e3af23c1c990807c4b0c1e7edd0bddf277996c439d (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Hainmueller_Hangartner_2019/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
    1.107542777 in [-0.09401291006, 1.72455622]?
    obrigatóriapassou[-0.09401291005604573,1.7245562202704523]1,107541.1075427774305522interval · [-0.09401291005604573, 1.7245562202704523]—call_6c9f0fdf
    2figura da resposta próxima
    1.107542777 vs 0.8152716551072032
    registradafalhou0,8152720.81527165510720321,107541.1075427774305522relativa 0.000001 · absoluta 4.639206965118617e-7crb_papers.q029.goldcall_6c9f0fdf
    3figura da resposta próxima
    0.06451484469 vs 0.46392069651186174
    registradafalhou0,4639210.463920696511861740,06451480.06451484468650168relativa 0.000001 · absoluta 4.639206965118617e-7crb_papers.q029.goldcall_6c9f0fdf

    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_6c9f0fdf)igual
    Argumentos da referência e do agente
    ArgumentoReferênciaAgente
    cluster"bfs"—diferente
    controls["group_treated","post"][]diferente
    dataset"ref_panel""ds_0015"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["g_post"]["indirect"]diferente
    y"nat_rate_ord""nat_rate_ord"igual

    Trajetória

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

    1. 0Início

      For municipalities that first moved to council-based naturalization decisions in 2006 or 2009, how much did ordinary naturalization rates change from 1991 to 2009 relative to municipalities that never changed their local decision regime?

      ds_0015 (agent)

      | Variable Name | Description | | --- | --- | | bfs | Swiss Federal Statistical Office (BFS) municipality code: a stable numeric identifier for each municipality in the panel. | | year | Calendar year of the observation (1991–2009). Institutional status is referenced as of January 1 of the given year, and annual rates are computed for the same year. | | nat_rate_ord | Ordinary naturalization rate (percent). Computed as the number of ordinary naturalizations recorded during the year divided by the stock of foreign residents who met statutory eligibility at the start of the year in the same municipality, multiplied by 100. Ordinary naturalizations refer to the standard pathway (as opposed to federally handled “facilitated” cases). | | indirect | Local decision procedure in place on January 1: 1 if applications were decided by the elected municipal council (representative/indirect democracy); 0 if applications were decided by citizens in a local vote (direct democracy). | Dataset Context: This dataset is an annual municipality–year panel for Switzerland that spans a period of institutional change in how local authorities decide on citizenship applications. Switzerland’s “triple citizenship” system assigns a central role to municipalities in evaluating and deciding ordinary naturalization requests. During the 1990s and 2000s, municipalities used different decision procedures: in some, citizens voted on applications (often at a citizens’ assembly and, historically in a few places, by ballot); in others, elected municipal councils rendered the decisions. A series of Swiss Federal Court rulings in 2003–2005 curtailed secret-ballot referendums for naturalizations and required municipalities to provide formal justifications for rejections. Several cantons subsequently updated their laws, and many municipalities revised or formalized their procedures, frequently shifting decision authority to municipal councils. The indicator in this file captures, for each municipality and year, which procedure was in force as of January 1. The panel combines two types of information. First, administrative registers from the Swiss Federal Statistical Office (PETRA: Foreign Population Structure and Migration Statistics) are used to derive annual ordinary naturalization rates. These rates are constructed as ordinary naturalizations completed within a year divided by the number of foreign residents who met the legal eligibility criteria at the start of that year, providing a comparable percentage measure across municipalities and over time. Second, the coding of local decision procedures relies on a nationwide survey of municipal head secretaries and systematic compilation of cantonal regulations and court decisions. The measurement convention aligns the institutional status to January 1 to enhance comparability across municipalities, recognizing that formal switches may occur during a calendar year. Ordinary naturalizations represent the standard route to citizenship and, in the study period, typically occurred after lengthy processing that could extend several years from initial application to final local vote. Facilitated naturalizations—handled centrally under federal law (for example, for certain spouses of Swiss citizens)—are not included in the numerator of the ordinary naturalization rate. The resulting dataset provides a consistent view of local institutions and annual naturalization activity across more than a decade and a half, covering the pre- and post-reform environment in which many municipalities updated their decision-making arrangements.

      file e9ce75e30cb08926da17f27cb91ecb80f964f077f9a592e052d672b61239e8f9 · frame —
      ref_first (reference)
      file e9ce75e30cb08926da17f27cb91ecb80f964f077f9a592e052d672b61239e8f9 · frame —
      1. select {"columns":["bfs","year","nat_rate_ord","indirect"]}
      2. dropna {"columns":["bfs","year","nat_rate_ord"]}
      3. filter {"query":"indirect == 1"}
      4. collapse {"aggs":[{"column":"year","fn":"min","name":"sw"}],"by":["bfs"]}
      ref_max (reference)
      file e9ce75e30cb08926da17f27cb91ecb80f964f077f9a592e052d672b61239e8f9 · frame —
      1. select {"columns":["bfs","year","nat_rate_ord","indirect"]}
      2. dropna {"columns":["bfs","year","nat_rate_ord"]}
      3. collapse {"aggs":[{"column":"indirect","fn":"max","name":"imax"}],"by":["bfs"]}
      ref_panel (reference)
      file e9ce75e30cb08926da17f27cb91ecb80f964f077f9a592e052d672b61239e8f9 · frame —
      1. select {"columns":["bfs","year","nat_rate_ord","indirect"]}
      2. dropna {"columns":["bfs","year","nat_rate_ord"]}
      3. filter {"query":"year in [1991, 2009]"}
      4. merge {"how":"left","on":["bfs"],"with":"ref_first"}
      5. merge {"how":"left","on":["bfs"],"with":"ref_years"}
      6. merge {"how":"left","on":["bfs"],"with":"ref_max"}
      7. filter {"query":"nyears == 2 and (sw in [2006, 2009] or imax == 0)"}
      8. derive {"args":{"cmp":"in","column":"sw","value":[2006,2009]},"name":"group_treated","op":"indicator"}
      9. derive {"args":{"column":"group_treated","default":0,"keep_unmapped":false,"mapping":[{"source":1,"target":1}]},"name":"group_treated","op":"map"}
      10. derive {"args":{"cmp":"eq","column":"year","value":2009},"name":"post","op":"indicator"}
      11. derive {"args":{"columns":["group_treated","post"]},"name":"g_post","op":"interaction"}
      ref_years (reference)
      file e9ce75e30cb08926da17f27cb91ecb80f964f077f9a592e052d672b61239e8f9 · frame —
      1. select {"columns":["bfs","year","nat_rate_ord","indirect"]}
      2. dropna {"columns":["bfs","year","nat_rate_ord"]}
      3. filter {"query":"year in [1991, 2009]"}
      4. collapse {"aggs":[{"column":"nat_rate_ord","fn":"count","name":"n"}],"by":["bfs","year"]}
      5. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["bfs"]}
    2. 1Turno do modelo
      call_afb39a38naive-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_0015",
          "x": [
            "indirect"
          ],
          "y": "nat_rate_ord"
        }
    3. 2Ferramenta
      infer.olsv0.1.0call_6c9f0fdfdecidido pelo modeloreexecutável

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

      Argumentos
      {
        "cluster": null,
        "controls": [],
        "dataset": "ds_0015",
        "fe": [],
        "intercept": true,
        "level": 0.95,
        "se": "HC1",
        "subset": null,
        "weights": null,
        "x": [
          "indirect"
        ],
        "y": "nat_rate_ord"
      }
      Figuras call_6c9f0fdf
      ChaveValorValor brutoErro-padrãoIC
      coef.indirect
      Coefficient on indirect in the regression of nat_rate_ord
      1,10754 1.10754277743055220,06451480.064514844686501680,981089 – 1,234
      Diagnósticos
      • n_obs = 22.97122971
      • k = 22
      • r2 = 0,01318350.013183467242530722
      • df_resid = 22.96922969
      • se_type = "HC1"
      • n_clusters = —
      Tabelas (1)
      {
        "coefficients": [
          {
            "ci_high": 2.163938338040925,
            "ci_low": 2.022415071555584,
            "coef": 2.0931767047982546,
            "p": 0,
            "se": 0.03610163501934651,
            "t": 57.98010820497581,
            "term": "Intercept"
          },
          {
            "ci_high": 1.2339962130150524,
            "ci_low": 0.981089341846052,
            "coef": 1.1075427774305522,
            "p": 1.1999450149136743e-65,
            "se": 0.06451484468650168,
            "t": 17.16725480488185,
            "term": "indirect"
          }
        ]
      }
      Digests dos dados
      ds_0015 b496d06ec0c7d2b154edeec08a7016063e29d7d7eba5abaf6e923cc1f6d5c7ee
      sha256 do resultado
      1a3711efbf596f04cfd5d90b135ae5c84241395d713d31ae1496b244bb19aa0e
    4. 3Turno do modelo
      call_fc4eace1naive-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.indirect = 1,108.",
          "caveats": [],
          "figure_refs": [
            "call_6c9f0fdf:coef.indirect"
          ]
        }
    5. 4Guarda
      resposta aceita
      Números encontrados
      1,108
      Sem lastro
      —
      Não citados
      —
      1 nova(s) tentativa(s) restante(s)
    6. 5Resposta

      Estimativa ingênua (infer.ols): coef.indirect = 1,108.

      Figuras citadas: call_6c9f0fdf:coef.indirect · Parada: answered
      Figura da resposta: call_6c9f0fdf:coef.indirect = 1,107541.1075427774305522 (se 0,06451480.06451484468650168)
    7. 6Pontuação
      #0resposta com lastropassouobrigatóriaevery number backed
    8. 7Pontuação
      #1figura da resposta próximapassouobrigatória1.107542777 in [-0.09401291006, 1.72455622]?
    9. 8Pontuação
      #2figura da resposta próximafalhouregistrada1.107542777 vs 0.8152716551072032
    10. 9Pontuação
      #3figura da resposta próximafalhouregistrada0.06451484469 vs 0.46392069651186174

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