{"attempt":1,"datasets":{"ds_0046":{"description_shown":"| Variable Name | Description |\n| --- | --- |\n| row_id | Row identifier / case index (sequential record number). |\n| educ | Education level (ordered categorical from the CCES; coded 1\u20136 with higher values indicating more education). |\n| votereg | Voter registration status (binary indicator; 1 = registered to vote, 0 = not registered). |\n| child18 | Child under age 18 present in household (binary indicator; 1 = yes, 0 = no). |\n| newsint | How closely respondent follows news about government and public affairs (ordinal scale; CCES item typically coded 1\u20134 with higher values = follows more closely). |\n| suppafford | Support for the Affordable Care Act (ACA) (dichotomous; 1 = support, 0 = oppose). |\n| dontcutmedicare | Budget-priority item: respondent selected \u201cDon\u2019t cut domestic spending such as Medicare and Social Security\u201d as the option they would least prefer among deficit-reduction choices (dichotomous; 1 = selected this option, 0 = otherwise). |\n| byr4647 | Indicator for birth cohort in this extract: 1 = born in 1946\u20131947, 0 = born in 1948\u20131949 (no other birth years included in this file). |\n| privpubins3r | Health insurance type (recoded dichotomy used in the study): 1 = has any public insurance (including public-only or public + private), 0 = private insurance only. (Respondents with other/none/unknown coverage may appear as missing, depending on CCES source coding.) |\n| con | Ideology: conservative (binary indicator; 1 = self-identifies as conservative, 0 = otherwise). |\n| mod | Ideology: moderate (binary indicator; 1 = self-identifies as moderate, 0 = otherwise). |\n| ideostrength | Strength of ideological identification (ordinal measure; higher values indicate stronger ideology). |\n| rep | Party identification: Republican (binary indicator; 1 = Republican, 0 = otherwise). |\n| ind | Party identification: Independent (binary indicator; 1 = Independent, 0 = otherwise). |\n| employed | Employment status (binary indicator; 1 = employed full-time or part-time, 0 = otherwise). |\n| healthcaresupport | Occupation indicator: works in \u201chealthcare support\u201d occupation category (binary indicator; 1 = yes, 0 = no). |\n| hcsocial | Industry indicator: works in \u201chealthcare or social assistance\u201d industry category (binary indicator; 1 = yes, 0 = no). |\n| fininsur | Industry indicator: works in \u201cfinance or insurance\u201d industry category (binary indicator; 1 = yes, 0 = no). |\n| hispanic2 | Hispanic ethnicity (binary indicator; 1 = Hispanic, 0 = not Hispanic). |\n| black | Race: Black/African American (binary indicator; 1 = Black, 0 = not Black). |\n| military | Military household affiliation (binary indicator; 1 = respondent or household member is affiliated with the military, 0 = otherwise). |\n| mobility | Residential mobility (binary indicator; 1 = recently moved, 0 = otherwise; exact reference period follows CCES coding). |\n| married | Marital status (binary indicator; 1 = married, 0 = not married). |\n| homeowner | Homeownership (binary indicator; 1 = owns home, 0 = does not own). |\n| labor | Labor union household indicator (binary indicator; 1 = respondent or someone in household belongs to a labor union, 0 = otherwise). |\n| publicemp | Public-sector employment (binary indicator; 1 = public employee, 0 = otherwise). |\n| vote08 | Self-reported voting in the 2008 election (binary indicator; 1 = voted, 0 = did not vote). |\n| bornagain | Religious identification as \u201cborn again\u201d (binary indicator; 1 = yes, 0 = no). |\n| religimp | Importance of religion (ordinal scale; higher values indicate religion is more important to the respondent). |\n| male | Gender (binary indicator; 1 = male, 0 = not male). |\n| fincome | Family income (ordered categorical bins from the CCES; coded 1\u201316 with higher values indicating higher income; some respondents may have missing/refused). |\n\nDataset Context:\nThis file is an analysis-ready extract derived from the 2012 Cooperative Congressional Election Study (CCES), an online national survey administered by YouGov/Polymetrix. It contains individual-level responses covering demographic characteristics (education, income, sex, race/ethnicity, marital and homeownership status), political identifiers and behavior (party identification, ideology and its strength, voter registration and 2008 turnout, news consumption), work/household indicators (employment, public-employee and military household flags, union household, mobility), religiosity measures, and items about health insurance source and attitudes toward health-related policy questions. Variable codings mix binary indicators and ordered categorical scales; the table above summarizes each column as present in the provided CSV.\n\nThis extract is restricted to respondents born in 1946\u20131949 (corresponding to roughly ages 63\u201366 at the time of the October\u2013November 2012 CCES field period).\n","file_sha256":"bb1eb952988798d36682e2840f8a80022fb48ddf3c93591bfca5793089f1ee30","frame_sha256":null,"role":"agent","transforms":[]},"ref_iv":{"description_shown":"","file_sha256":"bb1eb952988798d36682e2840f8a80022fb48ddf3c93591bfca5793089f1ee30","frame_sha256":null,"role":"reference","transforms":[{"args":{"columns":["suppafford","privpubins3r","byr4647","rep","ind","con","mod","ideostrength","hcsocial","fininsur","healthcaresupport","child18","male","married","labor","mobility","homeowner","religimp","employed","votereg","vote08","black","hispanic2","military","fincome","newsint","publicemp","bornagain"]},"op":"select"},{"args":{"columns":["suppafford","privpubins3r","byr4647","rep","ind","con","mod","ideostrength","hcsocial","fininsur","healthcaresupport","child18","male","married","labor","mobility","homeowner","religimp","employed","votereg","vote08","black","hispanic2","military","fincome","newsint","publicemp","bornagain"]},"op":"dropna"}]}},"epoch":1,"event":"sample_init","question":"What is the causal effect of being enrolled in public health insurance (versus only private insurance) on an individual's support for the Affordable Care Act, measured for the subgroup whose insurance enrollment was shifted by the exogenous eligibility variation exploited in this analysis?","question_sha256":"a16979f0a30252e26eecadc141382d0500cd133c51d0ad0540e7d6a9f1ee9abd","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":0,"skills":[],"task_id":"crb_papers.q076","task_sha256":"37a1386da06dd81ffb41c75b4b1148ea4aa592662c57b2fb5ceafdfa24c601c2","timestamp":"2026-10-15T17:10:29.434517Z"}
{"attempt":1,"attempts":[],"call_id":"call_12093871","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"naive-ols","model_requested":"naive-ols","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["9fcc390af7328ffe4d9021756a291c7374cc54830728b6a4349f140939a2e25c"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"c6cf747e2e0d8dbe2516121fed5798f8af94d33c1866bb9d9ae893494843a2c5","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","thoughts":null,"tool_calls":[{"args":{"dataset":"ds_0046","x":["privpubins3r"],"y":"suppafford"},"llm_name":"infer__ols","tool_id":"infer.ols","vendor_id":"script_1"}]},"response_id":null,"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":1,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.434517Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"arguments":{"cluster":null,"controls":[],"dataset":"ds_0046","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["privpubins3r"],"y":"suppafford"},"attempt":1,"cached":false,"call_id":"call_1421375d","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"ds_0046":"689c88964b32920f16710072893eca0946d0bfffd668f2f88d265ce3cc17f55f"},"decided_by":"model","duration_ms":5.090625025331974,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"a9fe2c4ae0e2f0344bf00a15b2f51220a6b63aef07123407f81e4d998a72578d","llm_name":"infer__ols","output_digest":"8e2f31de0dddadf372a917f5078c28a225b4fdb9f261ec068670680cf0238c55","rationale":"Linha de base ing\u00eanua: regress\u00e3o do resultado no tratamento, sem controles.","replay_class":"replayed","result":{"assumptions":["the conditional mean of the outcome is linear in the regressors","errors are independent across observations; their variance may differ"],"call_id":"call_1421375d","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":5221},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":0.0013166792116231507},{"flag":false,"name":"df_resid","note":"","value":5219},{"flag":false,"name":"se_type","note":"heteroskedasticity-robust standard errors (HC1)","value":"HC1"},{"flag":false,"name":"n_clusters","note":"errors not clustered","value":null}],"figures":[{"ci_high":0.06333452299721153,"ci_level":0.95,"ci_low":0.009162504753093052,"derivation":{"note_pt":"","steps":[{"formula":"","result":0.03624851387515229,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":5221.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de privpubins3r na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de suppafford.","unit":""},{"formula":"ep = \u221aV_jj","result":0.013816441377004055,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":0.0001908940523241897}],"text_pt":"Erro-padr\u00e3o robusto \u00e0 heterocedasticidade (HC1): a raiz da vari\u00e2ncia estimada do coeficiente.","unit":""},{"formula":"IC = \u03b2 \u00b1 c \u00b7 ep","result":null,"terms":[{"note":"","symbol":"\u03b2","unit":"","value":0.03624851387515229},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.960418633349461},{"note":"","symbol":"ep","unit":"","value":0.013816441377004055}],"text_pt":"Intervalo de 95% de confian\u00e7a: a estimativa mais ou menos o valor cr\u00edtico da distribui\u00e7\u00e3o t de Student com 5219 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.privpubins3r","label":"Coefficient on privpubins3r in the regression of suppafford","se":0.013816441377004055,"unit":"","value":0.03624851387515229}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":0.5311807465317487,"ci_low":0.49353338109643274,"coef":0.5123570638140907,"p":0.0,"se":0.009601868905671898,"t":53.36013945279314,"term":"Intercept"},{"ci_high":0.06333452299721153,"ci_low":0.009162504753093052,"coef":0.03624851387515229,"p":0.008726469612667265,"se":0.013816441377004055,"t":2.623578162136883,"term":"privpubins3r"}]},"tool":"infer.ols","version":"0.1.0","warnings":[]},"result_for_model_ref":"dc59eb07ac8ef1de12122945a1e3f9348e1badf4a7ecd47755eda7e10e86740e","result_sha256":"1da3e9706c759e9598f1f6495a7f8004a4947f70505292800e8f7b3a65f789e5","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":2,"synthetic":false,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.436897Z","tool_id":"infer.ols","turn_id":"call_12093871"}
{"attempt":1,"attempts":[],"call_id":"call_a1427c3b","epoch":1,"event":"model","finish_reason":"tool_use","latency_ms":0.0,"model_reported":"naive-ols","model_requested":"naive-ols","provider":"scripted","request":{"config":{},"contents_refs":[],"messages_refs":["9fcc390af7328ffe4d9021756a291c7374cc54830728b6a4349f140939a2e25c","6261c0611903f89cdfc87458d62c9cdd4720ac541e5b45c84d7b9179eb72b39f","11b015ac6eb4944bd613976833e6bd1fe8000ea599b328e621e9c9b6a1540c2c"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"c6cf747e2e0d8dbe2516121fed5798f8af94d33c1866bb9d9ae893494843a2c5","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"","thoughts":null,"tool_calls":[{"args":{"answer":"Estimativa ing\u00eanua (infer.ols): coef.privpubins3r = 0,03625.","caveats":[],"figure_refs":["call_1421375d:coef.privpubins3r"]},"llm_name":"submit_answer","tool_id":null,"vendor_id":"script_2"}]},"response_id":null,"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":3,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.442126Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"attempt":1,"call_id":"call_34ed126b","epoch":1,"event":"guard","numbers_found":["0,03625"],"retries_left":1,"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":4,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443644Z","turn_id":"call_a1427c3b","unbacked":[],"uncited":[],"verdict":"accepted"}
{"answer":"Estimativa ing\u00eanua (infer.ols): coef.privpubins3r = 0,03625.","answer_figure":{"call_id":"call_1421375d","ci_high":0.06333452299721153,"ci_low":0.009162504753093052,"formatted":0.03624851387515229,"key":"coef.privpubins3r","ref":"call_1421375d:coef.privpubins3r","se":0.013816441377004055,"tool_id":"infer.ols","unit":"","value":0.03624851387515229},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_1421375d:coef.privpubins3r"],"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":5,"stopped":"answered","task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443796Z"}
{"attempt":1,"check":{"check_index":0,"detail":"every number backed","expected":null,"failure_class":null,"kind":"answer_backed","observed":[],"passed":true,"required":true,"source_id":null,"tolerance":null,"trace_call_id":null,"weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":6,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443796Z"}
{"attempt":1,"check":{"check_index":1,"detail":"0.03624851388 in [0.001159492778, 0.09081768689]?","expected":[0.0011594927776589492,0.09081768688968336],"failure_class":null,"kind":"answer_figure_close","observed":0.03624851387515229,"passed":true,"required":true,"source_id":null,"tolerance":{"abs_tol":null,"interval":[0.0011594927776589492,0.09081768688968336],"min_lre":null,"open_interval":false,"rel_tol":null,"rule":"interval"},"trace_call_id":"call_1421375d","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":7,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443796Z"}
{"attempt":1,"check":{"check_index":2,"detail":"0.03624851388 vs 0.045988589833671156","expected":0.045988589833671156,"failure_class":null,"kind":"answer_figure_close","observed":0.03624851387515229,"passed":false,"required":false,"source_id":"crb_papers.q076.gold","tolerance":{"abs_tol":2.2871988293883776e-08,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":1e-06,"rule":null},"trace_call_id":"call_1421375d","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":8,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443796Z"}
{"attempt":1,"check":{"check_index":3,"detail":"0.01381644138 vs 0.022871988293883778","expected":0.022871988293883778,"failure_class":null,"kind":"answer_figure_close","observed":0.013816441377004055,"passed":false,"required":false,"source_id":"crb_papers.q076.gold","tolerance":{"abs_tol":2.2871988293883776e-08,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":1e-06,"rule":null},"trace_call_id":"call_1421375d","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":9,"task_id":"crb_papers.q076","timestamp":"2026-10-15T17:10:29.443796Z"}