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Tarefa causcibench_real.q077

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

Veredito

falhouDecidida pela verificação 1: figura da resposta próxima, fora da tolerância.
-0.006193464657 vs -0.017

Família do método (das chamadas de ferramentas): iv (two-stage least squares)

Pergunta feita ao analista

Among high-propensity voters, defined as those with a voting propensity greater than 0.68, what is the effect of receiving a get-out-the-vote phone call two weeks prior to the election on turnout?

Resposta

Estimativa (infer.iv_2sls): coef.contacted_2weeks = -0,006193.

Valores esperados e de onde vêm

causcibench_real.gold.q077

Fonte
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 77
Tipo
benchmark_gold
Localização
real_input.json, record id 77: fields effect and std_error
Trecho
id 77 effect -0.017 std_error 0.017
Valor como publicado
-0.017
Erro-padrão como publicado
0.017
Valor
-0,017-0.017 (se 0,0170.017)
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: -0,017-0.017 · relativa 0.05

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
-0.006193464657 vs -0.017
obrigatóriafalhou-0,017-0.017-0,00619346-0.006193464656590043relativa 0.05causcibench_real.gold.q077call_005ddf3f

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_005ddf3f)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"panagopoulos_timing""panagopoulos_timing"igual
endog["contacted_2weeks"]["contacted_2weeks"]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["two_weeks"]["two_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 high-propensity voters, defined as those with a voting propensity greater than 0.68, what is the effect of receiving a get-out-the-vote phone call two 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_b28760aereferenceFim: 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_2weeks"
        ],
        "exog": [
          "democrat",
          "republican",
          "unenrolled",
          "other_party",
          "age",
          "age_squared",
          "vtr_gen01",
          "vtr_gen03"
        ],
        "instruments": [
          "two_weeks"
        ],
        "y": "vtr_gen05"
      }
  3. 2Ferramenta
    infer.iv_2slsv0.1.0call_005ddf3fdecidido pelo modeloreexecutável

    Motivo: causcibench_metadata_rule/1: iv

    Argumentos
    {
      "cluster": null,
      "dataset": "panagopoulos_timing",
      "endog": [
        "contacted_2weeks"
      ],
      "exog": [
        "democrat",
        "republican",
        "unenrolled",
        "other_party",
        "age",
        "age_squared",
        "vtr_gen01",
        "vtr_gen03"
      ],
      "instruments": [
        "two_weeks"
      ],
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "y": "vtr_gen05"
    }
    Figuras call_005ddf3f
    ChaveValorValor brutoErro-padrãoIC
    coef.contacted_2weeks
    2SLS effect of contacted_2weeks on vtr_gen05
    -0,00619346 -0.0061934646565900430,01334470.013344682267538401-0,0323499 – 0,0199629
    Diagnósticos
    • first_stage_F.contacted_2weeks = 5.410,975410.969556892448
    • partial_r2.contacted_2weeks = 0,7197660.7197658679525261
    • weak_instrument = false
    • n_obs = 24.17124171
    • se_type = "HC1"
    • n_clusters = —
    Tabelas (3)
    {
      "coefficients": [
        {
          "ci_high": 0.028228790177920477,
          "ci_low": -0.0407434634331977,
          "coef": -0.006257336627638613,
          "p": 0.7221106237269574,
          "se": 0.017594404524171166,
          "t": -0.35564355810066167,
          "term": "Intercept"
        },
        {
          "ci_high": 0.048776015674020165,
          "ci_low": -0.01200362710373656,
          "coef": 0.0183861942851418,
          "p": 0.235689119057504,
          "se": 0.015504519076553534,
          "t": 1.185860341385631,
          "term": "democrat"
        },
        {
          "ci_high": 0.011363245874277408,
          "ci_low": -0.050238299441863414,
          "coef": -0.019437526783793003,
          "p": 0.21612073852452518,
          "se": 0.015714181440513786,
          "t": -1.2369417304600931,
          "term": "republican"
        },
        {
          "ci_high": -0.00028021096089355865,
          "ci_low": -0.06227696629288497,
          "coef": -0.031278588626889266,
          "p": 0.0479648492100454,
          "se": 0.015814997124021603,
          "t": -1.9777802285768245,
          "term": "unenrolled"
        },
        {
          "ci_high": 0.026168867235888675,
          "ci_low": -0.04544987488787545,
          "coef": -0.009640503825993385,
          "p": 0.5977244032058135,
          "se": 0.018269507729042508,
          "t": -0.5276827361181798,
          "term": "other_party"
        },
        {
          "ci_high": 0.005062684233877631,
          "ci_low": 0.003665205454028557,
          "coef": 0.004363944843953094,
          "p": 2.3591311461029977e-34,
          "se": 0.0003564883801715629,
          "t": 12.241478507245903,
          "term": "age"
        },
        {
          "ci_high": -0.000016526484273161066,
          "ci_low": -0.00002498565606855775,
          "coef": -0.000020756070170859407,
          "p": 7.29531174899702e-22,
          "se": 0.0000021578835359915916,
          "t": -9.618716591820869,
          "term": "age_squared"
        },
        {
          "ci_high": 0.30517646396614967,
          "ci_low": 0.275758742367123,
          "coef": 0.29046760316663633,
          "p": 0,
          "se": 0.007504282764356268,
          "t": 38.70691074519408,
          "term": "vtr_gen01"
        },
        {
          "ci_high": 0.35440874507459896,
          "ci_low": 0.3253140633331004,
          "coef": 0.3398614042038497,
          "p": 0,
          "se": 0.007421877251512969,
          "t": 45.791838464394985,
          "term": "vtr_gen03"
        },
        {
          "ci_high": 0.01996294229801841,
          "ci_low": -0.0323498716111985,
          "coef": -0.006193464656590043,
          "p": 0.6425696740961453,
          "se": 0.013344682267538401,
          "t": -0.46411480861226284,
          "term": "contacted_2weeks"
        }
      ],
      "first_stage": [
        {
          "ci_high": 0.7555774685812006,
          "ci_low": 0.7163562962807021,
          "coef": 0.7359668824309513,
          "endog": "contacted_2weeks",
          "instrument": "two_weeks",
          "p": 0,
          "se": 0.010005083714648276,
          "t": 73.5592927976639
        }
      ],
      "reduced_form": [
        {
          "ci_high": 0.014689353414644234,
          "ci_low": -0.023805723164157935,
          "coef": -0.004558184874756851,
          "instrument": "two_weeks",
          "p": 0.6425228432782131,
          "se": 0.009819861089868947,
          "t": -0.4641801786238591
        }
      ]
    }
    • 829 rows were dropped because one of 'vtr_gen05', 'contacted_2weeks', 'two_weeks', 'democrat', 'republican', 'unenrolled', 'other_party', 'age', 'age_squared', 'vtr_gen01', 'vtr_gen03' was missing
    Digests dos dados
    panagopoulos_timing a9840be060a94f8bcf5d9657e12a817f7e5a23d132aea3f8161124cbc615d87e
    sha256 do resultado
    873529595ac1f843a2bd8f56395d3a4f9fb10d76335ce396717d80e910cf65ea
  4. 3Turno do modelo
    call_f0c2311creferenceFim: 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_2weeks = -0,006193.",
        "caveats": [],
        "figure_refs": [
          "call_005ddf3f:coef.contacted_2weeks"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    -0,006193
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.iv_2sls): coef.contacted_2weeks = -0,006193.

    Figuras citadas: call_005ddf3f:coef.contacted_2weeks · Parada: answered
    Figura da resposta: call_005ddf3f:coef.contacted_2weeks = -0,00619346-0.006193464656590043 (se 0,01334470.013344682267538401)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta próximafalhouobrigatória-0.006193464657 vs -0.017

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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