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Tarefa causcibench_real.q079

causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01d

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
0.006643934363 vs -0.021

Família do método (das chamadas de ferramentas): Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E) · infer.iv_2sls (iv · mínimos quadrados em dois estágios)

Calculado pelo agente
coef.contacted_4weeks =0,006643930.006643934362992571
2SLS effect of contacted_4weeks on vtr_gen05
via infer.iv_2sls (call_46ce90b2)
Valor esperado (gabarito)
coef.contacted_4weeks =-0,021-0.021
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 79
Como foi validado
1 de 2 verificações obrigatórias aprovadas
relativa 0.05

Pergunta feita ao analista

Among low-propensity voters, defined as those with a voting propensity of at most 0.68, what is the effect of receiving a get-out-the-vote phone call four weeks prior to the election on turnout?

Resposta

Estimativa (infer.iv_2sls): coef.contacted_4weeks = 0,006644.

Como o agente resolveu e como foi validado

Resumo passo a passo do que o agente executou, por que o caminho está correto e como cada verificação conferiu o resultado.

  1. 1Preparação da base de dados
    panagopoulos_timing— The dataset consists of 25,000 registered voters in Rochester, New York, who were part of a randomized field experiment during the November 2005 municipal elections. Voters were randomly assigned to one of four groups: a phone reminder call scheduled for 4 weeks before Election Day, 2 weeks before, 3 days before, or a control group that received no call. The calls were nonpartisan get-out-the-vote reminders, delivered using standardized scripts. The unit of observation is the individual registered voter, and only those appearing on the official registration list were included. The main outcome is voter turnout in the 2005 election, while additional measures capture past voting history, party registration, demographics, and a predicted propensity to vote. The dataset also records whether each assigned reminder call was actually completed, allowing for comparison between group assignment and the reality of who was contacted. Data variables: vtr_gen01: Voted (2001) vtr_gen03: Voted (2003) vtr_gen05: Outcome: Voted 2005 treated: Successfully contacted four_weeks: Experimental group: Called 4 weeks before election two_weeks: Experimental group: Called 2 weeks before election three_days: Experimental group: Called 3 days before election control: Experimental group: Control, i.e., did not receive any calls democrat: Registered Democrat republican: Registered Republican unenrolled: Unaffiliated other_party: Other party registration age: Age (years) age_squared: Age squared contacted_4weeks: Successfully contacted: 4 weeks contacted_2weeks: Successfully contacted: 2 weeks contacted_3days: Successfully contacted: 3 days vote_prop: Predicted vote propensity use: Subject included id: Subject ID
  2. 2Chamada que gerou a resposta finalinfer.iv_2sls(Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E))citada na respostacoincide com a referência
    Ver chamada call_46ce90b2 nos detalhes

    causcibench_metadata_rule/1: iv

    Por que este é o caminho de referência: causcibench_metadata_rule/1: iv
    Argumentos principais
    dataset:
    "panagopoulos_timing"
    endog:
    ["contacted_4weeks"]
    exog:
    ["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]
    instruments:
    ["four_weeks"]
    level:
    0,950.95
    se:
    "HC1"
    y:
    "vtr_gen05"
    Resultado calculado
    • coef.contacted_4weeks = 0,00664393 0.006643934362992571
      2SLS effect of contacted_4weeks on vtr_gen05
    Diagnósticos: first_stage_F.contacted_4weeks = 5.499,415499.407794142408 (Wald F of the excluded instruments in the first stage for contacted_4weeks (heteroskedasticity-robust standard errors (HC1))) · partial_r2.contacted_4weeks = 0,7227830.722782547537601 (share of the variation the instruments explain beyond the controls) · weak_instrument = false (every first-stage F is at least 10) · n_obs = 24.17124171 · se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
  3. 3Conferência de lastro e resposta final

    Todos os 1 números escritos na resposta foram conferidos contra as ferramentas e o enunciado (nenhum número sem lastro).

    Números encontrados: 0,006644
    Figuras citadas: call_46ce90b2:coef.contacted_4weeks
    • #0resposta com lastro
      every number in the answer was stated by a tool call
    • #1figura da resposta próxima
      CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|

Aprofundamento técnico para especialistas

Acesso direto às fontes primárias, tabela formal de verificações, comparação de argumentos, trajetória completa com prompts brutos e somas SHA-256.

Valores esperados e de onde vêm

causcibench_real.gold.q079

Fonte
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 79
Tipo
benchmark_gold
Localização
real_input.json, record id 79: fields effect and std_error
Trecho
id 79 effect -0.021 std_error 0.021
Valor como publicado
-0.021
Erro-padrão como publicado
0.021
Valor
-0,021-0.021 (se 0,0210.021)
Conferido por
arquivo do benchmark · Written by scripts/freeze_causcibench_real.py from the pinned file; equal to the `answer` and `std_error` of the same id in data/metadata_csv/real_input.csv at the pin.
sha256 da cópia lida
c1f4c8930675afff63d816d8ed066941ae92697e7bfc31e9d38519398dd80438 (identifica a cópia lida, não um arquivo canônico)
Endereço
https://raw.githubusercontent.com/causalNLP/CauSciBench/d9bb43a2d90f261978cc5ac0b628c0484f6e8956/data/metadata_json/real_input.json
Licença
CauSciBench repository (MIT for code; metadata as published in the repository)
  • #1 figura da resposta próxima: -0,021-0.021 · relativa 0.05
Especificação técnica do gabarito

CauSciBench real_input.json @ d9bb43a, id 79: effect -0.021

Verificações

Cada verificação, o que esperava, o que observou e a chamada que leu
#VerificaçãoObrigatóriaResultadoEsperadoObservadoTolerânciaFonteChamada
0
resposta com lastro
every number in the answer was stated by a tool call
every number backed
obrigatóriapassou0 sem lastro0 sem lastro[]———
1
figura da resposta próxima
CauSciBench effect accuracy: |answer figure − gold| ≤ 5% of |gold|
0.006643934363 vs -0.021
obrigatóriafalhou-0,021-0.0210,006643930.006643934362992571relativa 0.05causcibench_real.gold.q079call_46ce90b2

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 · metadata_rule

Referência: infer.iv_2slsChamada do agente: infer.iv_2sls (call_46ce90b2)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"panagopoulos_timing""panagopoulos_timing"igual
endog["contacted_4weeks"]["contacted_4weeks"]igual
exog["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]["democrat","republican","unenrolled","other_party","age","age_squared","vtr_gen01","vtr_gen03"]igual
instruments["four_weeks"]["four_weeks"]igual
level—0,950.95não fixado pela referência
se—"HC1"não fixado pela referência
subset——não fixado pela referência
y"vtr_gen05""vtr_gen05"igual

Pendências do caminho de referência: needs_spec:sample, needs_spec:subgroup

Trajetória

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

  1. 0Início

    Among low-propensity voters, defined as those with a voting propensity of at most 0.68, what is the effect of receiving a get-out-the-vote phone call four weeks prior to the election on turnout?

    panagopoulos_timing (agent)

    The dataset consists of 25,000 registered voters in Rochester, New York, who were part of a randomized field experiment during the November 2005 municipal elections. Voters were randomly assigned to one of four groups: a phone reminder call scheduled for 4 weeks before Election Day, 2 weeks before, 3 days before, or a control group that received no call. The calls were nonpartisan get-out-the-vote reminders, delivered using standardized scripts. The unit of observation is the individual registered voter, and only those appearing on the official registration list were included. The main outcome is voter turnout in the 2005 election, while additional measures capture past voting history, party registration, demographics, and a predicted propensity to vote. The dataset also records whether each assigned reminder call was actually completed, allowing for comparison between group assignment and the reality of who was contacted. Data variables: vtr_gen01: Voted (2001) vtr_gen03: Voted (2003) vtr_gen05: Outcome: Voted 2005 treated: Successfully contacted four_weeks: Experimental group: Called 4 weeks before election two_weeks: Experimental group: Called 2 weeks before election three_days: Experimental group: Called 3 days before election control: Experimental group: Control, i.e., did not receive any calls democrat: Registered Democrat republican: Registered Republican unenrolled: Unaffiliated other_party: Other party registration age: Age (years) age_squared: Age squared contacted_4weeks: Successfully contacted: 4 weeks contacted_2weeks: Successfully contacted: 2 weeks contacted_3days: Successfully contacted: 3 days vote_prop: Predicted vote propensity use: Subject included id: Subject ID

    file 37ac4466ad26ac40012073e833298d7e3f2f8e8fbe8eb1fa90268ec2e1181ad7 · frame —
  2. 1Turno do modelo
    call_10cff27dreferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Texto visível

    causcibench_metadata_rule/1: iv

    Chamadas pedidas
    • infer.iv_2sls
      {
        "dataset": "panagopoulos_timing",
        "endog": [
          "contacted_4weeks"
        ],
        "exog": [
          "democrat",
          "republican",
          "unenrolled",
          "other_party",
          "age",
          "age_squared",
          "vtr_gen01",
          "vtr_gen03"
        ],
        "instruments": [
          "four_weeks"
        ],
        "y": "vtr_gen05"
      }
  3. 2Ferramenta
    infer.iv_2sls— Variáveis instrumentais por mínimos quadrados em dois estágios (MQ2E)v0.1.0call_46ce90b2decidido pelo modeloreexecutável

    Motivo: causcibench_metadata_rule/1: iv

    Argumentos
    {
      "cluster": null,
      "dataset": "panagopoulos_timing",
      "endog": [
        "contacted_4weeks"
      ],
      "exog": [
        "democrat",
        "republican",
        "unenrolled",
        "other_party",
        "age",
        "age_squared",
        "vtr_gen01",
        "vtr_gen03"
      ],
      "instruments": [
        "four_weeks"
      ],
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "y": "vtr_gen05"
    }
    Figuras call_46ce90b2
    ChaveValorValor brutoErro-padrãoIC
    coef.contacted_4weeks
    2SLS effect of contacted_4weeks on vtr_gen05
    0,006643930.0066439343629925710,01321330.013213288842595752-0,0192549 – 0,0325428
    Diagnósticos
    • first_stage_F.contacted_4weeks = 5.499,415499.407794142408 (Wald F of the excluded instruments in the first stage for contacted_4weeks (heteroskedasticity-robust standard errors (HC1)))
    • partial_r2.contacted_4weeks = 0,7227830.722782547537601 (share of the variation the instruments explain beyond the controls)
    • weak_instrument = false (every first-stage F is at least 10)
    • n_obs = 24.17124171
    • se_type = "HC1" (heteroskedasticity-robust standard errors (HC1))
    • n_clusters = — (errors not clustered)
    Derivação matemática e pressupostos
    coef.contacted_4weeks
    1. Com um instrumento e um regressor endógeno, o MQ2E é a razão entre o coeficiente de four_weeks na forma reduzida (vtr_gen05 sobre four_weeks e os controles) e no primeiro estágio (contacted_4weeks sobre four_weeks e os controles).β = ρ / π→ 0,00664393 (0.006643934362992571)
    2. Erro-padrão robusto à heterocedasticidade (HC1): a raiz da variância estimada do coeficiente.ep = √V_jj→ 0,0132133 (0.013213288842595752)
    3. Intervalo de 95% de confiança: a estimativa mais ou menos o valor crítico da distribuição t de Student com 24161 graus de liberdade vezes o erro-padrão.IC = β ± c · ep
    Pressupostos do estimador
    • the instruments affect the outcome only through the endogenous regressors (exclusion restriction)
    • the instruments are as good as randomly assigned given the controls
    • errors are independent across observations; their variance may differ
    Tabelas (3)
    {
      "coefficients": [
        {
          "ci_high": 0.027872443677130012,
          "ci_low": -0.04115845159245117,
          "coef": -0.00664300395766058,
          "p": 0.7059965609120944,
          "se": 0.017609363656386618,
          "t": -0.3772427037845445,
          "term": "Intercept"
        },
        {
          "ci_high": 0.048833565842174145,
          "ci_low": -0.011983943758936806,
          "coef": 0.01842481104161867,
          "p": 0.2349983315768399,
          "se": 0.015514178674047566,
          "t": 1.187611115530084,
          "term": "democrat"
        },
        {
          "ci_high": 0.011434537536520299,
          "ci_low": -0.05020709231399498,
          "coef": -0.019386277388737338,
          "p": 0.21763322717590783,
          "se": 0.015724406762669032,
          "t": -1.2328781416900174,
          "term": "republican"
        },
        {
          "ci_high": -0.00027646047903795434,
          "ci_low": -0.06230406495382598,
          "coef": -0.03129026271643197,
          "p": 0.047992603691157876,
          "se": 0.0158228665536715,
          "t": -1.9775343873560922,
          "term": "unenrolled"
        },
        {
          "ci_high": 0.026128104977695507,
          "ci_low": -0.045517316663666235,
          "coef": -0.009694605842985362,
          "p": 0.5958072944833109,
          "se": 0.018276313512535808,
          "t": -0.5304464621016589,
          "term": "other_party"
        },
        {
          "ci_high": 0.005053852839255821,
          "ci_low": 0.0036570374163414745,
          "coef": 0.004355445127798648,
          "p": 2.941922814542331e-34,
          "se": 0.00035631916183168804,
          "t": 12.223437845467313,
          "term": "age"
        },
        {
          "ci_high": -0.000016496533777673516,
          "ci_low": -0.00002494900480483445,
          "coef": -0.000020722769291253983,
          "p": 7.8688979403636335e-22,
          "se": 0.000002156174210563032,
          "t": -9.610897482092941,
          "term": "age_squared"
        },
        {
          "ci_high": 0.30514576659555614,
          "ci_low": 0.27572806354808443,
          "coef": 0.2904369150718203,
          "p": 0,
          "se": 0.007504278031966839,
          "t": 38.70284574140412,
          "term": "vtr_gen01"
        },
        {
          "ci_high": 0.3543533597286071,
          "ci_low": 0.3252583311200153,
          "coef": 0.3398058454243112,
          "p": 0,
          "se": 0.007421965735209465,
          "t": 45.78380681714655,
          "term": "vtr_gen03"
        },
        {
          "ci_high": 0.032542802035281815,
          "ci_low": -0.019254933309296673,
          "coef": 0.006643934362992571,
          "p": 0.6150938991910406,
          "se": 0.013213288842595752,
          "t": 0.5028221544339879,
          "term": "contacted_4weeks"
        }
      ],
      "first_stage": [
        {
          "ci_high": 0.7582130109020783,
          "ci_low": 0.7191645970289074,
          "coef": 0.7386888039654929,
          "endog": "contacted_4weeks",
          "instrument": "four_weeks",
          "p": 0,
          "se": 0.00996101408525058,
          "t": 74.1579921123975
        }
      ],
      "reduced_form": [
        {
          "ci_high": 0.024047353687358525,
          "ci_low": -0.014231753830910106,
          "coef": 0.0049077999282242084,
          "instrument": "four_weeks",
          "p": 0.6152481524341317,
          "se": 0.009764768689421126,
          "t": 0.5026027839800424
        }
      ]
    }
    • 829 rows were dropped because one of 'vtr_gen05', 'contacted_4weeks', 'four_weeks', 'democrat', 'republican', 'unenrolled', 'other_party', 'age', 'age_squared', 'vtr_gen01', 'vtr_gen03' was missing
    Hashes SHA-256 e metadados de reprodução
    Digests dos dados
    panagopoulos_timing a9840be060a94f8bcf5d9657e12a817f7e5a23d132aea3f8161124cbc615d87e
    sha256 do resultado
    5bafe4a039fdd91f50782770b314cca7cdccb4911684fed1220f8a898661eec0
  4. 3Turno do modelo
    call_dc0d7eaareferenceFim: tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cache
    Chamadas pedidas
    • submit_answer (meta-ferramenta)
      {
        "answer": "Estimativa (infer.iv_2sls): coef.contacted_4weeks = 0,006644.",
        "caveats": [],
        "figure_refs": [
          "call_46ce90b2:coef.contacted_4weeks"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    0,006644
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.iv_2sls): coef.contacted_4weeks = 0,006644.

    Figuras citadas: call_46ce90b2:coef.contacted_4weeks · Parada: answered
    Figura da resposta: call_46ce90b2:coef.contacted_4weeks = 0,006643930.006643934362992571 (se 0,01321330.013213288842595752)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta próximafalhouobrigatória0.006643934363 vs -0.021

Épocas × verificações

Resultado de cada verificação em cada época pontuada
#01
Época 1passoufalhou

Tentativas

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

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