{"args":{},"checks":[{"abs_tol":null,"bind":"any","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"answer_backed","min_lre":null,"note":"every number traced to a tool call or the question","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":null,"value":null,"weight":1.0,"where":null},{"abs_tol":null,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":true,"key":null,"kind":"answer_figure_close","min_lre":null,"note":"CRB estimate_within_solution_ci: the answer figure inside the gold 95% interval effect \u00b1 1.96\u00b7|SE| of source crb_papers.q117.gold (closed, evaluate_result.py; no --auto-rescale)","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":null,"value":[0.004128055008715298,0.36554412060967345],"weight":1.0,"where":null},{"abs_tol":9.219797591861176e-08,"bind":"answer_call","column":null,"failure_class":null,"field":"value","interval":false,"key":null,"kind":"answer_figure_close","min_lre":null,"note":"replication cell: the gold effect to rel 1e-6 (abs floor 1e-6\u00b7SE); never required","open_interval":false,"rel_tol":1e-06,"required":false,"source_id":"crb_papers.q117.gold","table":null,"tool":null,"value":0.18483608780919436,"weight":1.0,"where":null},{"abs_tol":9.219797591861176e-08,"bind":"answer_call","column":null,"failure_class":null,"field":"se","interval":false,"key":null,"kind":"answer_figure_close","min_lre":null,"note":"replication cell: the gold SE to rel 1e-6; never required","open_interval":false,"rel_tol":1e-06,"required":false,"source_id":"crb_papers.q117.gold","table":null,"tool":null,"value":0.09219797591861177,"weight":1.0,"where":null}],"datasets":{"ds_0082":{"columns":null,"description":"| Variable Name | Description |\n| --- | --- |\n| (unnamed) | Row index carried over from the CSV export; not a substantive variable. |\n| petpooled | Indicator equal to 1 if the House member signed at least one civil-rights\u2013related discharge petition during the **78th Congress (1943\u20131944)**; 0 otherwise. |\n| Dvotespercent | Democratic candidate\u2019s share of the **two-party vote** in the general election immediately preceding service in the 78th Congress (i.e., the **1942** U.S. House election for the district/seat), coded as a proportion from 0 to 1 (e.g., 0.50 = 50%). |\n| icpsr | ICPSR numeric identifier for the member of the U.S. House of Representatives. |\n\nDataset Context:\nThis file contains member-level records from the U.S. House of Representatives for the **78th Congress (1943\u20131944)**. Each observation corresponds to a single House member/district in that Congress and includes (i) whether the member signed any civil-rights\u2013related discharge petition(s) during the Congress, (ii) the district\u2019s Democratic two-party vote share in the immediately preceding House election (1942), and (iii) a stable legislator identifier. Because this extract includes only one Congress, there is **no separate Congress/session/year column** in the file.\n\nThe data were assembled by combining archival records of discharge petition signatures (from National Archives holdings on House discharge petitions), historical U.S. House election returns (two-party vote shares by district), and ICPSR legislator identification codes. The broader underlying project described in the accompanying documentation spans multiple Congresses across the mid-20th century (1933\u20131976) and compiles repeated measures of legislative activity and election results; this benchmark CSV is a single-Congress subset for 1943\u201344.\n","file_sha256":"b3af3d8d86f85721c10f0046184627dc0c3982250018ee826277a302ca85839f","format":"csv","frame_sha256":null,"generator":null,"kind":"file","licence":"redistributed by CausalReasoningBenchmark (MIT) under the original replication data's terms","member":null,"object":null,"params":{},"path":null,"read_kw":{},"records":null,"role":"agent","sha256":"b3af3d8d86f85721c10f0046184627dc0c3982250018ee826277a302ca85839f","transforms":[],"url":"https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/data/ds_0082/data/data.csv"}},"difficulty":"M","id":"crb_papers.q117","level":"T2","meta":{"agent_reach":{"blocked_by":["no_reference_path","no_tool:rdrobust_robust_bias_corrected","needs_op:rdrobust_cluster_variance"],"dtypes":{"ds_0082":{"petpooled":"int64"}},"named":{"outcome":["petpooled"],"treatment":[]},"reachable":false,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":null,"unit_scale":1.0},"cluster":"ds_0082","crb":{"data_path":"data/ds_0082/data/data.csv","dataset_id":"ds_0082","gold":{"ci95":[0.004128055008715298,0.36554412060967345],"ci_rule":"effect \u00b1 1.96\u00b7|standard_error| (evaluate_result.ci_bounds)","effect":0.18483608780919436,"standard_error":0.09219797591861177},"identification":{"causal_quantity":"CATE","cutoff":0.5,"outcomes":["petpooled"],"running_variable":"Dvotespercent","strategy":"Regression Discontinuity","treatments":[],"variant":"sharp"},"identification_strategy":"Regression Discontinuity"},"naive":{"dataset":"ds_0082","treatment":"Dvotespercent","y":"petpooled"},"native_id":"117","reference_path":{"calls":[],"needs":["no_tool:rdrobust_robust_bias_corrected","needs_op:rdrobust_cluster_variance"],"provenance":"none","quotes":{},"reference_datasets":[],"source_id":"crb_papers.q117.script"}},"question":"Among U.S. House districts with very close elections around the 50% Democratic vote threshold in the 78th Congress, what is the causal effect of electing a Democrat (versus a Republican) on the probability that the representative signs a civil-rights discharge petition?","requires":[],"runner":null,"sources":["crb_papers.q117.gold","crb_papers.q117.script"],"split":"public","suite":"crb_papers","tags":["econ-bench","external","crb","rd","ref_none"],"target":"agent","tool":null,"truth":"CausalReasoningBenchmark gold at the pinned revision: causal_queries.json effect and standard_error (the value the item's estimation.py prints), scored as evaluate_result.py scores estimate_within_solution_ci"}