{"attempt":1,"datasets":{"ds_0056":{"description_shown":"| Variable Name   | Description                                                                                         |\n|-----------------|-----------------------------------------------------------------------------------------------------|\n| Unnamed: 0      | Row index carried over from the source file.                                                        |\n| contact         | Indicator that the respondent (or someone in the household) reported contacting their U.S. House office. |\n| rspartywon      | Indicator that the party the respondent identifies with currently holds the district\u2019s House seat.  |\n| rspartywinperc  | Vote-share margin for the respondent\u2019s party in the most recent U.S. House general election (negative if loss). |\n| distname        | Congressional district name (e.g., \u201cStateNumber,\u201d such as \u201cAlabama1\u201d).                             |\n| distencoded     | Numeric code for the congressional district.                                                         |\n| margin          | District vote margin from the most recent U.S. House election (same coding as rspartywinperc).      |\n| pknowl          | Political knowledge score based on correct responses to a knowledge battery (scaled 0\u20131).           |\n| church          | Self-reported frequency of attending religious services (scaled).                                    |\n| churchmr        | Mean-replaced version of church (original missing values filled with the sample mean).              |\n| churchmiss      | Missingness flag for church (1 if church was missing in the raw data, 0 otherwise).                 |\n| dempidstr       | Strength of Democratic Party identification (scaled).                                                |\n| dempidstrmr     | Mean-replaced version of dempidstr.                                                                  |\n| dempidstrmiss   | Missingness flag for dempidstr.                                                                      |\n| reppidstr       | Strength of Republican Party identification (scaled).                                                |\n| reppidstrmr     | Mean-replaced version of reppidstr.                                                                  |\n| reppidstrmiss   | Missingness flag for reppidstr.                                                                      |\n| age             | Respondent age in years.                                                                             |\n| agemr           | Mean-replaced version of age.                                                                        |\n| actscale        | Composite scale of political activity/engagement (scaled).                                           |\n| actscalemr      | Mean-replaced version of actscale.                                                                   |\n| actscalemiss    | Missingness flag for actscale.                                                                       |\n| followpol       | Self-reported attention to or following of politics (scaled).                                        |\n| followpolmr     | Mean-replaced version of followpol.                                                                  |\n| followpolmiss   | Missingness flag for followpol.                                                                      |\n| incomecat       | Household income category (ordered category, scaled for analysis).                                   |\n| incomecatmr     | Mean-replaced version of incomecat.                                                                  |\n| incomecatmiss   | Missingness flag for incomecat.                                                                      |\n| donategen       | Indicator for having made a political/campaign donation.                                             |\n| donategenmr     | Mean-replaced version of donategen.                                                                  |\n| donategenmiss   | Missingness flag for donategen.                                                                      |\n\nData Description: The dataset consists of respondent-level records from the 2008 Cooperative Congressional Election Study (CCES), fielded online by YouGov/Polimetrix in October\u2013November 2008, matched to U.S. House district identifiers and district-level general election returns from the most recent contest at the time (the 2006 U.S. House elections, compiled from CQ Press). Each record links a survey respondent to their congressional district and includes whether they reported contacting their current U.S. House member\u2019s office, their party identification strength, political knowledge, religious attendance, age, political engagement, attention to politics, income category, and whether they report having made political donations.\n\nTo provide district context, the file includes the district name/code and the party-aligned vote margin from the prior House election. Variables are typically scaled to 0\u20131 for analysis. For several measures the dataset includes a trio of columns: the original variable, a mean-replaced version used when handling missing survey responses, and a corresponding missingness indicator. The data support analyses of patterns in citizen communication with congressional offices alongside individual characteristics and district electoral context.","file_sha256":"c1f14f16b11509dc4d8acf60197a5e836b849f3231553c39c4f0aaf9e5124868","frame_sha256":null,"role":"agent","transforms":[]}},"epoch":1,"event":"sample_init","question":"Among voters in U.S. House districts decided at an infinitesimally small margin, what is the average effect of being represented by a copartisan, compared to an outpartisan, on the probability of reporting contact with the representative?","question_sha256":"b197029a66080564cc783c7abbb10f182c54f8be12c0d5ad6aa6f42f31a2dec6","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":0,"skills":[],"task_id":"crb_papers.q087","task_sha256":"39260b45636873f688a67648805cee40577d6e5c4b1106edf5e259a02f24bfd3","timestamp":"2026-10-15T17:10:29.889400Z"}
{"attempt":1,"attempts":[],"call_id":"call_1e775a44","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":["907dfdbd3f5517bb8d3f419b978f92458b9e09c304794cfa7ecf49bfba9edda6"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"c930d083fecda30be70000614f2afa1f96d07e06c941410979d134e199ea7943","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_0056","x":["rspartywon"],"y":"contact"},"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.q087","timestamp":"2026-10-15T17:10:29.889400Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"arguments":{"cluster":null,"controls":[],"dataset":"ds_0056","fe":[],"intercept":true,"level":0.95,"se":"HC1","subset":null,"weights":null,"x":["rspartywon"],"y":"contact"},"attempt":1,"cached":false,"call_id":"call_b4784048","card_version":"0.1.0","code_version":"2925aeab2262","dataset_digests":{"ds_0056":"d8648b0bc4e09bc117bf735e324619d9776db36fe1ab495db94aa5e863b4282f"},"decided_by":"model","duration_ms":18.964500166475773,"epoch":1,"error":null,"event":"tool","informed_by":[],"input_digest":"76896d1f48a98664538cdbfe6f85f2e7866baef334140b3c5eb04bc99920d50a","llm_name":"infer__ols","output_digest":"f4843d0b23f5195738bd515015418bdc27f08dbf3f345ff9b68c70c4b6b46890","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_b4784048","datasets":{},"diagnostics":[{"flag":false,"name":"n_obs","note":"observations used","value":32617},{"flag":false,"name":"k","note":"parameters estimated, fixed-effect dummies included","value":2},{"flag":false,"name":"r2","note":"","value":0.0005380081180881291},{"flag":false,"name":"df_resid","note":"","value":32615},{"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":0.03413070514513335,"ci_level":0.95,"ci_low":0.012448726470041523,"derivation":{"note_pt":"","steps":[{"formula":"","result":0.023289715807587437,"terms":[{"note":"","symbol":"n","unit":"observa\u00e7\u00f5es","value":32617.0},{"note":"","symbol":"k","unit":"par\u00e2metros","value":2.0}],"text_pt":"Coeficiente de rspartywon na regress\u00e3o por m\u00ednimos quadrados ordin\u00e1rios de contact.","unit":""},{"formula":"ep = \u221aV_jj","result":0.005531013379257855,"terms":[{"note":"diagonal da matriz de covari\u00e2ncia","symbol":"V_jj","unit":"","value":3.0592109001529395e-05}],"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":0.023289715807587437},{"note":"quantil 0.975","symbol":"c","unit":"","value":1.9600367227823532},{"note":"","symbol":"ep","unit":"","value":0.005531013379257855}],"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 32615 graus de liberdade vezes o erro-padr\u00e3o.","unit":""}]},"key":"coef.rspartywon","label":"Coefficient on rspartywon in the regression of contact","se":0.005531013379257855,"unit":"","value":0.023289715807587437}],"notes":"","reason":"","status":"ok","tables":{"coefficients":[{"ci_high":0.3435799520854038,"ci_low":0.3261162075866981,"coef":0.33484807983605097,"p":0.0,"se":0.004454953393402552,"t":75.1630938119208,"term":"Intercept"},{"ci_high":0.03413070514513335,"ci_low":0.012448726470041523,"coef":0.023289715807587437,"p":2.5520588328049997e-05,"se":0.005531013379257855,"t":4.210750220733045,"term":"rspartywon"}]},"tool":"infer.ols","version":"0.1.0","warnings":["130 rows were dropped because one of 'contact', 'rspartywon' was missing"]},"result_for_model_ref":"284cbbb246498096ce9f9e7d9c5133fa3f64436c014e424dd50bdd5e339dc607","result_sha256":"5c60f4eb022f4eefe96eca59f7ea320aaa710e6b7a4e248330d0405b06593f40","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":2,"synthetic":false,"task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.892363Z","tool_id":"infer.ols","turn_id":"call_1e775a44"}
{"attempt":1,"attempts":[],"call_id":"call_a66963e8","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":["907dfdbd3f5517bb8d3f419b978f92458b9e09c304794cfa7ecf49bfba9edda6","e30943ec9a41b60da03c6d4b1658cdcd7390c4411cc134092ac31f5c3fe0f5a4","f6b6f0a3d59ec45d03f941613f83a6fd3449a2172b743b149d320ab53ce627b7"],"system_stable_ref":"433a6877aa6a378bbd4b7e2752e484d8cb7499c562d68222be231f62ff2fa420","system_task_ref":"c930d083fecda30be70000614f2afa1f96d07e06c941410979d134e199ea7943","tools_ref":"52ab03d8ec104abb85572294bf8a469d75c5de9e74d6042caabff8017adc572b"},"response":{"text":"","thoughts":null,"tool_calls":[{"args":{"answer":"Estimativa ing\u00eanua (infer.ols): coef.rspartywon = 0,02329.","caveats":[],"figure_refs":["call_b4784048:coef.rspartywon"]},"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.q087","timestamp":"2026-10-15T17:10:29.911492Z","usage":{"cached":0,"input":0,"output":0,"thoughts":0},"vendor":false}
{"attempt":1,"call_id":"call_c00124e8","epoch":1,"event":"guard","numbers_found":["0,02329"],"retries_left":1,"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":4,"task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.913213Z","turn_id":"call_a66963e8","unbacked":[],"uncited":[],"verdict":"accepted"}
{"answer":"Estimativa ing\u00eanua (infer.ols): coef.rspartywon = 0,02329.","answer_figure":{"call_id":"call_b4784048","ci_high":0.03413070514513335,"ci_low":0.012448726470041523,"formatted":0.023289715807587437,"key":"coef.rspartywon","ref":"call_b4784048:coef.rspartywon","se":0.005531013379257855,"tool_id":"infer.ols","unit":"","value":0.023289715807587437},"attempt":1,"caveats":[],"epoch":1,"event":"answer","figure_refs":["call_b4784048:coef.rspartywon"],"run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":5,"stopped":"answered","task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.913424Z"}
{"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.q087","timestamp":"2026-10-15T17:10:29.913424Z"}
{"attempt":1,"check":{"check_index":1,"detail":"0.02328971581 in [0.2518100685, 0.2604484642]?","expected":[0.2518100685486893,0.26044846416312634],"failure_class":"out_of_tolerance","kind":"answer_figure_close","observed":0.023289715807587437,"passed":false,"required":true,"source_id":null,"tolerance":{"abs_tol":null,"interval":[0.2518100685486893,0.26044846416312634],"min_lre":null,"open_interval":false,"rel_tol":null,"rule":"interval"},"trace_call_id":"call_b4784048","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":7,"task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.913424Z"}
{"attempt":1,"check":{"check_index":2,"detail":"0.02328971581 vs 0.2561292663559078","expected":0.2561292663559078,"failure_class":null,"kind":"answer_figure_close","observed":0.023289715807587437,"passed":false,"required":false,"source_id":"crb_papers.q087.gold","tolerance":{"abs_tol":2.2036723506216945e-09,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":1e-06,"rule":null},"trace_call_id":"call_b4784048","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":8,"task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.913424Z"}
{"attempt":1,"check":{"check_index":3,"detail":"0.005531013379 vs 0.0022036723506216947","expected":0.0022036723506216947,"failure_class":null,"kind":"answer_figure_close","observed":0.005531013379257855,"passed":false,"required":false,"source_id":"crb_papers.q087.gold","tolerance":{"abs_tol":2.2036723506216945e-09,"interval":null,"min_lre":null,"open_interval":false,"rel_tol":1e-06,"rule":null},"trace_call_id":"call_b4784048","weight":1.0},"epoch":1,"event":"score","run_id":"20261015T171027Z-suite-crb_papers-naive-54c3f2","seq":9,"task_id":"crb_papers.q087","timestamp":"2026-10-15T17:10:29.913424Z"}