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Tarefa crb_papers.q057

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

For districts that moved from no Section 5 preclearance coverage in analysis period 1 to coverage in period 2 and remained covered in period 3, how did gaining coverage affect the representative's civil-rights support score between periods 1 and 3, relative to districts covered in all three periods?

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.q057.gold

Fonte
CausalReasoningBenchmark, causal_queries.json, index 57 (revision edd0fe1c1d1c)
Tipo
benchmark_gold
Localização
causal_queries.json['57'].effect and .standard_error
Trecho
index 57: effect 0.383051, standard_error 0.0929923
Valor como publicado
0.3830510450811192
Erro-padrão como publicado
0.09299225335317234
Valor
0,3830510.3830510450811192 (se 0,09299230.09299225335317234)
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: 0,3830510.3830510450811192 · relativa 0.000001 · absoluta 9.299225335317233e-8
  • #3 figura da resposta próxima: 0,09299230.09299225335317234 · relativa 0.000001 · absoluta 9.299225335317233e-8

crb_papers.q057.script

Fonte
CausalReasoningBenchmark reference estimation script for index 57
Tipo
software
Localização
solutions/research_papers/DiD/Schuit_Rogowski_2017/question_1/estimation.py
Valor
—
Conferido por
arquivo do benchmark · sha256 of the script's 4754 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
a8b8cf513298f0d2564d181dd08492cbab47f5251b996971ec5bbec392d27fbe (identifica a cópia lida, não um arquivo canônico)
Endereço
https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/solutions/research_papers/DiD/Schuit_Rogowski_2017/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[0.20078622850890143,0.5653158616533369]—interval · [0.20078622850890143, 0.5653158616533369]——
    2figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,3830510.3830510450811192—relativa 0.000001 · absoluta 9.299225335317233e-8crb_papers.q057.gold—
    3figura da resposta próxima
    no answer figure: the answer cites no effect of an estimator call
    registradafalhou0,09299230.09299225335317234—relativa 0.000001 · absoluta 9.299225335317233e-8crb_papers.q057.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

      For districts that moved from no Section 5 preclearance coverage in analysis period 1 to coverage in period 2 and remained covered in period 3, how did gaining coverage affect the representative's civil-rights support score between periods 1 and 3, relative to districts covered in all three periods?

      ds_0030 (agent)

      | Variable Name | Description | | --- | --- | | party | Member’s party identification using standard congressional numeric codes (e.g., 100 = Democrat, 200 = Republican; other parties/independents use their conventional codes). Party is measured for the member serving in that Congress (two-year House term). | | correct | Civil-rights roll-call support score for the member in that Congress (two-year House term). Constructed as the proportion (0–1) of included civil-rights–related House roll calls on which the member voted in the direction coded as expanding (rather than restricting) civil rights; abstentions are treated as votes to restrict civil rights. The set of roll calls varies by Congress. | | dpres | District presidential partisanship: Democratic presidential vote share for the most recent presidential election prior to (or associated with) the Congress observation. Higher values indicate greater support for the Democratic presidential candidate (scale follows the replication file’s coding/transformation of election returns). | | percentblack | Share of the congressional district population that is Black (0–1), aligned to district boundaries within redistricting cycles using decennial census data and standard crosswalk/harmonization to congressional districts. | | competitive | Electoral competitiveness measure based on the margin of victory in the most recent presidential election in the district, multiplied by −1 so that larger values correspond to closer (more competitive) contests. Scale reflects the transformation used in the replication files. | | covered_new2 | Indicator (1/0) that the congressional district contained any geographic overlap with a jurisdiction subject to Section 5 preclearance during that Congress. Coverage is based on the list of covered states/counties/townships and subsequent changes due to statutory amendments and court actions (including “bail-in” and “bail-out”). Time-varying at the district–Congress level. | | black_legis | Indicator (1/0) that the district’s U.S. House member was Black in that Congress, based on congressional rosters/biographical sources. | | redistrict_decade | District identifier that is stable within a redistricting cycle (roughly a decade). This ID is intended to allow districts to be tracked consistently within-cycle despite renumbering or boundary changes across cycles. | | year3 | Ordered analysis-period index taking values 1 through 5. Use it with redistrict_decade to order observations within a district-cycle. The extract does not retain calendar years, Congress numbers, or a separate redistricting-cycle label; an index value must not be interpreted as a unique calendar Congress across the whole study. Periods named in the questions refer to these recorded index values. | | treatment | Inverse-coded coverage indicator: 1 means not covered by Section 5 preclearance and 0 means covered. In every row, treatment = 1 - covered_new2. Either existing column determines coverage, provided its coding is respected; gaining coverage means covered_new2 changes from 0 to 1, or treatment changes from 1 to 0. Neither column is an ever-covered flag. | Dataset Context: This file contains 902 district-period observations for 261 district-cycle identifiers, with at most five ordered analysis periods per identifier. It is an unbalanced extract: some units appear in only one period. The source analysis for this extract concerns Texas and the Deep South states of Alabama, Georgia, Louisiana, Mississippi, and South Carolina. It is not the full national panel. The parent collection covers House terms from 1959–60 through 1997–98, but this extract does not preserve the calendar Congress labels needed to date each row. Questions therefore specify windows using year3 rather than asserting calendar dates. The observational unit is a congressional district in a House term, with districts tracked inside redistricting cycles using redistrict_decade. The parent collection includes representatives who served the full Congress in single-member districts. Do not join different redistrict_decade identifiers as if their district boundaries were unchanged. Missing periods are absent observations, not zeros or evidence that a district was uncovered. Legislative behavior is summarized with a civil-rights support score. To build it, House roll-call votes were identified from policy agenda categories focused on civil rights, minority issues, and voting rights, and votes not directly pertinent to these topics were excluded. For each Congress-member pair, the score is the proportion of included roll calls on which the member voted in the direction coded as expanding civil rights, yielding a value between 0 and 1. Jurisdictional coverage under the Voting Rights Act’s Section 5 preclearance provision is mapped to congressional districts by geographic overlap. Coverage operated at the state, county, or township level and changed over time due to statutory amendments and court actions, including “bail-in” (placing additional jurisdictions under review) and “bail-out” (removing jurisdictions meeting statutory criteria). A district is flagged as covered in a given Congress if any part of it overlapped a covered jurisdiction during that period. District context draws on administrative sources. Demographic composition, including the share of the population that is Black, comes from the U.S. Census, harmonized to congressional boundaries within each redistricting cycle. Presidential election returns are used to compute district-level Democratic vote strength and a competitiveness proxy based on recent presidential margins. Member characteristics, including party codes and whether the representative is Black, come from standard congressional rosters and roll-call archives. The observed coverage histories include districts covered throughout a window, districts moving into coverage, and districts moving out of coverage. Six district-cycle units move from uncovered in period 1 to covered in period 2 and remain covered in period 3. There are no units observed in both periods 1 and 2 that remain uncovered in both. The questions identify their respective observation windows and use districts covered throughout those windows as the comparison population. These recorded histories describe the available data; they do not by themselves establish that the groups would have followed the same outcome trends.

      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      ref_c1 (reference)
      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
      2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
      3. filter {"query":"year3 == 1"}
      4. rename {"map":{"covered_new2":"c1"}}
      5. select {"columns":["redistrict_decade","c1"]}
      ref_c2 (reference)
      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
      2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
      3. filter {"query":"year3 == 2"}
      4. rename {"map":{"covered_new2":"c2"}}
      5. select {"columns":["redistrict_decade","c2"]}
      ref_c3 (reference)
      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
      2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
      3. filter {"query":"year3 == 3"}
      4. rename {"map":{"covered_new2":"c3"}}
      5. select {"columns":["redistrict_decade","c3"]}
      ref_panel (reference)
      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
      2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
      3. filter {"query":"year3 in [1, 3]"}
      4. dropna {"columns":["correct"]}
      5. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c1"}
      6. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c2"}
      7. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_c3"}
      8. filter {"query":"(c1 == 0 and c2 == 1 and c3 == 1) or (c1 == 1 and c2 == 1 and c3 == 1)"}
      9. merge {"how":"inner","on":["redistrict_decade"],"with":"ref_years"}
      10. filter {"query":"nyears == 2"}
      11. derive {"args":{"cmp":"eq","column":"c1","value":0},"name":"gained_coverage","op":"indicator"}
      12. derive {"args":{"cmp":"eq","column":"year3","value":3},"name":"post","op":"indicator"}
      13. derive {"args":{"columns":["gained_coverage","post"]},"name":"gained_post","op":"interaction"}
      ref_years (reference)
      file 04dd7c4cc12ed66ead5ebdb56002ef0ce3382585e7404e50c3fea64977886219 · frame —
      1. select {"columns":["redistrict_decade","year3","correct","covered_new2"]}
      2. dropna {"columns":["redistrict_decade","year3","covered_new2"]}
      3. filter {"query":"year3 in [1, 3]"}
      4. dropna {"columns":["correct"]}
      5. collapse {"aggs":[{"column":"correct","fn":"count","name":"n"}],"by":["redistrict_decade","year3"]}
      6. collapse {"aggs":[{"column":"n","fn":"count","name":"nyears"}],"by":["redistrict_decade"]}
    2. 1Turno do modelo
      call_805ac554rules-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

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    #0123
    Época 1passoufalhoufalhoufalhou

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