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Tarefa causcibench_real.q069

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

Veredito

passouPassou em todas as verificações obrigatórias.

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

Pergunta feita ao analista

Does PEPFAR funding increase approval of U.S. leadership?

Resposta

Estimativa (infer.iv_2sls): coef.x = 0,2016.

Valores esperados e de onde vêm

causcibench_real.gold.q069

Fonte
CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 69
Tipo
benchmark_gold
Localização
real_input.json, record id 69: fields effect and std_error
Trecho
id 69 effect 0.202 std_error 0.068
Valor como publicado
0.202
Erro-padrão como publicado
0.068
Valor
0,2020.202 (se 0,0680.068)
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: 0,2020.202 · 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
0.2016168029 vs 0.202
obrigatóriapassou0,2020.2020,2016170.2016168028931283relativa 0.05causcibench_real.gold.q069call_95801693

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_95801693)igual
Argumentos da referência e do agente
ArgumentoReferênciaAgente
cluster——não fixado pela referência
dataset"goldsmith_doing_well""goldsmith_doing_well"igual
endog["x"]["x"]igual
exog["usaid","gdppc","wbgi","fhscore","africa","trade_i","trade_e","unvote_key"]["usaid","gdppc","wbgi","fhscore","africa","trade_i","trade_e","unvote_key"]igual
instruments["z_ratio","z_death"]["z_ratio","z_death"]igual
level—0,950.95não fixado pela referência
se—"HC1"não fixado pela referência
subset——não fixado pela referência
y"y_us""y_us"igual

Trajetória

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

  1. 0Início

    Does PEPFAR funding increase approval of U.S. leadership?

    goldsmith_doing_well (agent)

    The dataset combines multinational survey data on public opinion with country-level information on aid flows, health indicators, governance, and economic conditions. Public opinion measures come from the Gallup World Poll (GWP), an annual global survey launched in 2006 that samples individuals aged 15 and older. In countries with high telephone penetration (over 80%), data are collected through Random-Digit-Dial (RDD) telephone interviews; elsewhere, surveys are conducted face-to-face. Each survey includes about 1,000 respondents per country per year. Aid-related data include figures from the U.S. President's Emergency Plan for AIDS Relief (PEPFAR), one of the largest U.S. bilateral health initiatives, launched in 2003 and first disbursed in 2004, aimed at combating HIV/AIDS in dozens of countries, especially in Sub-Saharan Africa. The dataset also incorporates U.S. Official Development Assistance (ODA) compiled from international aid databases. Additional country-level indicators are drawn from international sources: population and economic statistics from the World Bank's World Development Indicators (WDI), health data from UNAIDS and global monitoring agencies, governance measures from the World Bank Governance Indicators, civil liberties scores from Freedom House, UN General Assembly voting data, and trade flows from the U.S. Department of Commerce. Data variables: country: Country name ccode: Numeric country code y_us: Net approval of the U.S. (log(%approve) - log(%disapprove)) y_ch: Net approval of China y_fr: Net approval of France y_ge: Net approval of Germany y_in: Net approval of India y_ja: Net approval of Japan y_ru: Net approval of Russia y_uk: Net approval of the U.K. y_ownc: Net approval of respondent's own country x: PEPFAR funds per capita (log) x_imputed: PEPFAR funds per capita (log, imputed) z_ratio: HIV prevalence rate (log) z_death: HIV-related deaths per capita (log) usaid: U.S. ODA per capita (log) usaid_imputed: U.S. ODA per capita (log, imputed) gdppc: GDP per capita (log) wbgi: World Bank governance indicator fhscore: Freedom House civil liberties score africa: 1 if African country, 0 otherwise trade_i: Imports to the U.S. (log) trade_e: Exports to the U.S. (log) unvote_key: UN voting alignment with the U.S.

    file e45a2c15808d35983e45405dd1eb70737617764feccf2852c6c51ba329b094dc · frame —
  2. 1Turno do modelo
    call_9b58f99dreferenceFim: 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": "goldsmith_doing_well",
        "endog": [
          "x"
        ],
        "exog": [
          "usaid",
          "gdppc",
          "wbgi",
          "fhscore",
          "africa",
          "trade_i",
          "trade_e",
          "unvote_key"
        ],
        "instruments": [
          "z_ratio",
          "z_death"
        ],
        "y": "y_us"
      }
  3. 2Ferramenta
    infer.iv_2slsv0.1.0call_95801693decidido pelo modeloreexecutável

    Motivo: causcibench_metadata_rule/1: iv

    Argumentos
    {
      "cluster": null,
      "dataset": "goldsmith_doing_well",
      "endog": [
        "x"
      ],
      "exog": [
        "usaid",
        "gdppc",
        "wbgi",
        "fhscore",
        "africa",
        "trade_i",
        "trade_e",
        "unvote_key"
      ],
      "instruments": [
        "z_ratio",
        "z_death"
      ],
      "level": 0.95,
      "se": "HC1",
      "subset": null,
      "y": "y_us"
    }
    Figuras call_95801693
    ChaveValorValor brutoErro-padrãoIC
    coef.x
    2SLS effect of x on y_us
    0,201617 0.20161680289312830,07539450.075394481570921680,0499427 – 0,353291
    Diagnósticos
    • first_stage_F.x = 25,508925.508852768251494
    • partial_r2.x = 0,4514590.45145917151222803
    • weak_instrument = false
    • overid_p = 0,3457980.3457975250962223
    • sargan = 0,8888190.8888190860442153
    • sargan_df = 11
    • n_obs = 5757
    • se_type = "HC1"
    • n_clusters = —
    Tabelas (3)
    {
      "coefficients": [
        {
          "ci_high": 7.8977616887121265,
          "ci_low": 0.2810032976934078,
          "coef": 4.089382493202767,
          "p": 0.035890660011518125,
          "se": 1.8930767509615973,
          "t": 2.1601778644872933,
          "term": "Intercept"
        },
        {
          "ci_high": 0.0419619322175393,
          "ci_low": -0.255633484831684,
          "coef": -0.10683577630707236,
          "p": 0.1552557603276624,
          "se": 0.07396466269337133,
          "t": -1.4444164607357415,
          "term": "usaid"
        },
        {
          "ci_high": 0.10472757863965182,
          "ci_low": -0.7151251846946072,
          "coef": -0.3051988030274777,
          "p": 0.1408761453518549,
          "se": 0.20376702605005767,
          "t": -1.4977830758176849,
          "term": "gdppc"
        },
        {
          "ci_high": 0.3902976879919897,
          "ci_low": -1.4453650453833893,
          "coef": -0.5275336786956998,
          "p": 0.2534144322784223,
          "se": 0.4562374523074205,
          "t": -1.1562699993779526,
          "term": "wbgi"
        },
        {
          "ci_high": 0.0837604042568798,
          "ci_low": -0.5844022236347064,
          "coef": -0.2503209096889133,
          "p": 0.13841118107678746,
          "se": 0.16606580802332532,
          "t": -1.5073597188275725,
          "term": "fhscore"
        },
        {
          "ci_high": 1.5072591608424075,
          "ci_low": 0.10020905622278065,
          "coef": 0.8037341085325941,
          "p": 0.0260402996208304,
          "se": 0.3497096407356625,
          "t": 2.2982898236429183,
          "term": "africa"
        },
        {
          "ci_high": 0.277077323734156,
          "ci_low": -0.11624003415204469,
          "coef": 0.08041864479105566,
          "p": 0.4148608857009515,
          "se": 0.0977554896374261,
          "t": 0.8226509333575784,
          "term": "trade_i"
        },
        {
          "ci_high": 0.23641770243626825,
          "ci_low": -0.33977667608061435,
          "coef": -0.05167948682217305,
          "p": 0.7198134085002114,
          "se": 0.1432079273108187,
          "t": -0.3608702939328758,
          "term": "trade_e"
        },
        {
          "ci_high": 2.5064564978937827,
          "ci_low": -0.5660250799866152,
          "coef": 0.9702157089535838,
          "p": 0.21015332447655968,
          "se": 0.7636376453402579,
          "t": 1.2705184387829385,
          "term": "unvote_key"
        },
        {
          "ci_high": 0.35329093598100364,
          "ci_low": 0.04994266980525297,
          "coef": 0.2016168028931283,
          "p": 0.010272245995103067,
          "se": 0.07539448157092168,
          "t": 2.674158621323929,
          "term": "x"
        }
      ],
      "first_stage": [
        {
          "ci_high": 1.7243983105177778,
          "ci_low": 0.3368998966929577,
          "coef": 1.0306491036053678,
          "endog": "x",
          "instrument": "z_ratio",
          "p": 0.00446407948881963,
          "se": 0.34465235419304974,
          "t": 2.9904020415542307
        },
        {
          "ci_high": 0.4983168856705443,
          "ci_low": -0.4747560604950842,
          "coef": 0.01178041258773006,
          "endog": "x",
          "instrument": "z_death",
          "p": 0.9613392159101395,
          "se": 0.24170974060651668,
          "t": 0.04873784795833938
        }
      ],
      "reduced_form": [
        {
          "ci_high": 0.45277687069189726,
          "ci_low": -0.3732109219697897,
          "coef": 0.039782974361053755,
          "instrument": "z_ratio",
          "p": 0.8471089345405091,
          "se": 0.2051740271837986,
          "t": 0.1938986864327396
        },
        {
          "ci_high": 0.4513912862000947,
          "ci_low": -0.19064539286118695,
          "coef": 0.1303729466694539,
          "instrument": "z_death",
          "p": 0.41786647218140255,
          "se": 0.15948086910367892,
          "t": 0.8174832969131747
        }
      ]
    }
    • 96 rows were dropped because one of 'y_us', 'x', 'z_ratio', 'z_death', 'usaid', 'gdppc', 'wbgi', 'fhscore', 'africa', 'trade_i', 'trade_e', 'unvote_key' was missing
    Digests dos dados
    goldsmith_doing_well 86960799c51564c41b8eff9ae72ea65bbe56b8bf41e1fd2d667fac0748f19b98
    sha256 do resultado
    3f74877bb896b89b028d407bb0db2efbecd1bbe1d511dac89b809913244648ec
  4. 3Turno do modelo
    call_a4aea0eareferenceFim: 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.x = 0,2016.",
        "caveats": [],
        "figure_refs": [
          "call_95801693:coef.x"
        ]
      }
  5. 4Guarda
    resposta aceita
    Números encontrados
    0,2016
    Sem lastro
    —
    Não citados
    —
    1 nova(s) tentativa(s) restante(s)
  6. 5Resposta

    Estimativa (infer.iv_2sls): coef.x = 0,2016.

    Figuras citadas: call_95801693:coef.x · Parada: answered
    Figura da resposta: call_95801693:coef.x = 0,2016170.2016168028931283 (se 0,07539450.07539448157092168)
  7. 6Pontuação
    #0resposta com lastropassouobrigatóriaevery number backed
  8. 7Pontuação
    #1figura da resposta próximapassouobrigatória0.2016168029 vs 0.202

Épocas × verificações

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

Tentativas

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

Downloads desta tarefa

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