Tarefa causcibench_real.q040
causcibench_realagentT2publicépoca 1, tentativa 1Execução: 20261015T171059Z-suite-causcibench_real-scripted-ded01dVeredito
Família do método (das chamadas de ferramentas): iv (two-stage least squares)
Pergunta feita ao analista
Does an increase in trust in local government increase citizens' willingness to co-produce policy with local government?
Estimativa (infer.iv_2sls): coef.trust = 1,275.
Valores esperados e de onde vêm
causcibench_real.gold.q040
- Fonte
- CauSciBench real split, data/metadata_json/real_input.json at d9bb43a, id 40
- Tipo
- benchmark_gold
- Localização
- real_input.json, record id 40: fields effect and std_error
- Trecho
id 40 effect 1.275 std_error 1.445
- Valor como publicado
1.275- Erro-padrão como publicado
1.445- Valor
- 1,275
1.275(se 1,4451.445) - 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: 1,275
1.275· relativa 0.05
Verificações
| # | Verificação | Obrigatória | Resultado | Esperado | Observado | Tolerância | Fonte | Chamada |
|---|---|---|---|---|---|---|---|---|
| 0 | resposta com lastro every number backed | obrigatória | passou | — | [] | — | — | — |
| 1 | figura da resposta próxima 1.275193082 vs 1.275 | obrigatória | passou | 1,2751.275 | 1,275191.275193081701345 | relativa 0.05 | causcibench_real.gold.q040 | call_bb1f48e5 |
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
| Argumento | Referência | Agente | |
|---|---|---|---|
| cluster | — | — | não fixado pela referência |
| dataset | "liu_public_trust2" | "liu_public_trust2" | igual |
| endog | ["trust"] | ["trust"] | igual |
| exog | [] | [] | igual |
| instruments | ["trustprime"] | ["trustprime"] | igual |
| level | — | 0,950.95 | não fixado pela referência |
| se | — | "HC1" | não fixado pela referência |
| subset | — | — | não fixado pela referência |
| y | "coproduce" | "coproduce" | igual |
Trajetória
Cada evento na ordem em que aconteceu: turnos do modelo, chamadas de ferramentas, guardas, transformações e pontuação.
- 0Início
Does an increase in trust in local government increase citizens' willingness to co-produce policy with local government?
liu_public_trust2(agent)The dataset comes from a pre-registered vignette experiment examining the effect of trust in government on perceived collaborative governance in a hypothetical environmental program. Respondents were randomly assigned to three experimental conditions: Corrupt, Control, and Honest, about government integrity in a fictional U.S. city, Midtown. The information provided to the corrupt group explicitly states that the (hypothetical) municipality has corrupt officials. Similarly, for the honest group, the information states that officials are not corrupt. The control group is provided with no information. After reading the information about government integrity, subjects reported trust in government, perceptions of collaborative governance, and willingness to coproduce public services. Variables: trust: Trust in government (0-100; 0=never, 100=always) PPP: Support for public-private partnerships (0-100; 0=never, 100=always) PCP: Support for public-citizen partnerships (0-100; 0=never, 100=always) coproduce: Willingness to coproduce public services (0-100; 0=never, 100=always) placebo1: Placebo outcome variable for robustness checks (0-100; 0=never, 100=always) placebo2: Placebo outcome variable for robustness checks (0-100; 0=never, 100=always) duration: Time spent on the survey sex: 0=male; 1=female white: Race indicator (1=yes, 0=no) black: Race indicator (1=yes, 0=no) hispanic: Race indicator (1=yes, 0=no) asian: Race indicator (1=yes, 0=no) other: Race indicator (1=yes, 0=no) age: Age in years (18-100) income: 1=<25k; 2=25k-34,999; 3=35k-49,999; 4=50k-74,999; 5=75k-99,999; 6=100k-149,999; 7=150k+ education: 1=<high school; 2=high school/GED; 3=some college; 4=2-year degree; 5=4-year degree; 6=master's; 7=doctoral; 8=professional (JD, MD) ideology: 1=very liberal; 2=liberal; 3=moderate; 4=conservative; 5=very conservative gw: Belief that global warming is happening (-1=no, 0=don't know, 1=yes) gwh: Belief about human causation of global warming (-1=neither, 0=mostly natural, 1=mostly human) covid: Concern about COVID-19 (1=not at all, ..., 5=extremely concerned) covid_job: Concern about job loss due to the pandemic (1=strongly disagree, ..., 5=strongly agree) rand: The randomly assigned government integrity group: Corrupt, Control, and Honest trustprime: Encoding of government integrity group to which participants are assigned (0=Corrupt, 1=Control, 2=Honest) at: Response to the question, ""What is 17 + 63 equal to?"" The question was meant to test the attentiveness of the participants atpass: 1 = participant provided correct answer to attention test question, 0 otherwise mc: Response to the manipulation check question: Have you seen the information below from any previous part of this survey? ""Local and state government have more corruption than we assumed"" mcpass: 1 = participant passed the manipulation check, 0 = otherwise mcatpass: 1 = passed both attention and manipulation test, 0 = otherwise climatebelief: Average of gw and gwh"
filefc860c838198dcffd59dcd954f0a1f1743f18b6fdb1a88ee81b4490493d3c3cf· frame — - 1Turno do modelo
call_31561d2ereferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheTexto visívelcauscibench_metadata_rule/1: iv
Chamadas pedidasinfer.iv_2sls{ "dataset": "liu_public_trust2", "endog": [ "trust" ], "exog": [], "instruments": [ "trustprime" ], "y": "coproduce" }
- 2Ferramenta
infer.iv_2slsv0.1.0call_bb1f48e5decidido pelo modeloreexecutávelMotivo: causcibench_metadata_rule/1: iv
Argumentos
{ "cluster": null, "dataset": "liu_public_trust2", "endog": [ "trust" ], "exog": [], "instruments": [ "trustprime" ], "level": 0.95, "se": "HC1", "subset": null, "y": "coproduce" }Figuras call_bb1f48e5 Chave Valor Valor bruto Erro-padrão IC coef.trust 2SLS effect of trust on coproduce1,27519 1.2751930817013451,44568 1.4456821144241951-1,56086 – 4,11125 Diagnósticosfirst_stage_F.trust= 135,729135.72900899797403partial_r2.trust= 0,09584360.0958435875458935weak_instrument=falsen_obs= 1.3371337se_type="HC1"n_clusters= —
Tabelas (3)
{ "coefficients": [ { "ci_high": 78.15924368120673, "ci_low": 52.919859113995564, "coef": 65.53955139760114, "p": 1.5833876480442728e-23, "se": 6.432899298602477, "t": 10.188182397296249, "term": "Intercept" }, { "ci_high": 4.111249201514859, "ci_low": -1.5608630381121689, "coef": 1.275193081701345, "p": 0.3778976463335493, "se": 1.4456821144241951, "t": 0.8820701791757626, "term": "trust" } ], "first_stage": [ { "ci_high": 0.6315374020998727, "ci_low": 0.44950510693073226, "coef": 0.5405212545153025, "endog": "trust", "instrument": "trustprime", "p": 6.082820714072249e-30, "se": 0.04639556169835534, "t": 11.650279352786956 } ], "reduced_form": [ { "ci_high": 2.2307400704311706, "ci_low": -0.8522021418902871, "coef": 0.6892689642704418, "instrument": "trustprime", "p": 0.38053943356430475, "se": 0.7857662591757105, "t": 0.8771933844467986 } ] }- Digests dos dados
liu_public_trust2075a3e2ce885dad588f2e9e6bee224ee62b6c7eb389d59cb0f989acf9a8d97b6- sha256 do resultado
aed3da62d16edf3f7fa28e0cd199a44970b607e1b607595214b41bacb234497e
- 3Turno do modelo
call_8fa1f1fareferenceFim:tool_use0 ms0 de entrada · 0 de saída · 0 de raciocínio · 0 em cacheChamadas pedidassubmit_answer(meta-ferramenta){ "answer": "Estimativa (infer.iv_2sls): coef.trust = 1,275.", "caveats": [], "figure_refs": [ "call_bb1f48e5:coef.trust" ] }
- 4Guardaresposta aceita
- Números encontrados
- 1,275
- Sem lastro
- —
- Não citados
- —
1 nova(s) tentativa(s) restante(s) - 5Resposta
Estimativa (infer.iv_2sls): coef.trust = 1,275.
Figuras citadas:call_bb1f48e5:coef.trust· Parada:answeredFigura da resposta:call_bb1f48e5:coef.trust= 1,275191.275193081701345(se 1,445681.4456821144241951) - 6Pontuação#0resposta com lastropassouobrigatória
every number backed - 7Pontuação#1figura da resposta próximapassouobrigatória
1.275193082 vs 1.275
Épocas × verificações
| # | 0 | 1 |
|---|---|---|
| Época 1 | passou | passou |
Tentativas
Cada tentativa é seu próprio arquivo e é publicada; só a última de cada época é pontuada.
- época 1, tentativa 1passoupontuada(exibindo)
Downloads desta tarefa
cea579c105918ba0fc24315fb44cef087f9c9c399159017ca4aee91fc2fd0d8dO hash de um zip é só de transporte: o que ancora a integridade é o RUN_SHA256SUMS que vai dentro dele, cópia exata do SHA256SUMS da execução.
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| native/causcibench_real/causcibench_real.q040.e1.a1.json | 1,7 KB | 03aaae4d38f817488349855a6d4aa91effa6eae1bf5ff54eb9ba20c0b4044e7f |
| sources/causcibench_real.gold.q040.json | 1,2 KB | ecc55d4a184cacec54c3315094859b979eea39a2a1eda73afcc28d38664b3d14 |
| specs/causcibench_real.q040.json | 6,8 KB | 528239382fc0feecd8b4e1999b2d6f0cb5c9ca6db8a2be503c60be48a7cff952 |
| traces/causcibench_real.q040.e1.a1.jsonl | 15,6 KB | defa7c3b240a81d8853db15a123d6b20d55f88dc4dccf9bf36b272003add124a |
| trajectories/causcibench_real.q040.e1.a1.jsonl | 12,2 KB | 4c75e4b387bf4dfa7daef410ed0179e78b434f984126af6478695fdb54fbd363 |