{"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.q114.gold (closed, evaluate_result.py; no --auto-rescale)","open_interval":false,"rel_tol":null,"required":true,"source_id":null,"table":null,"tool":null,"value":[-0.03665507940386209,0.6919657798441574],"weight":1.0,"where":null},{"abs_tol":1.858726681755152e-07,"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.q114.gold","table":null,"tool":null,"value":0.3276553502201477,"weight":1.0,"where":null},{"abs_tol":1.858726681755152e-07,"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.q114.gold","table":null,"tool":null,"value":0.1858726681755152,"weight":1.0,"where":null}],"datasets":{"ds_0079":{"columns":null,"description":"| Variable Name | Description |\n| --- | --- |\n| Unnamed: 0 | Row identifier for the candidate observation (index carried over from the source CSV; not a substantive variable). |\n| d_board0 | Binary indicator equal to 1 if the individual ever served as a director on the board of at least one publicly traded corporation observed in BoardEx during 2000\u20132013, excluding any board positions held before the candidate\u2019s first Senate election; 0 otherwise. |\n| margin | Vote margin in the candidate\u2019s first U.S. Senate general election used for the dataset, measured as (candidate vote share \u2212 0.50). Units are vote-share proportion (e.g., 0.03 = 3 percentage points above 50%; \u22120.03 = 3 points below 50%). |\n| everwon | Binary indicator equal to 1 if the candidate ever went on to hold U.S. Senate office at any point (i.e., ultimately won a Senate election and served), and 0 otherwise. This can differ from the first-election result captured by `margin` (e.g., a candidate with a negative first-election `margin` may later win and thus have `everwon = 1`). |\n\nDataset Context:\nThis dataset is a candidate-level file focused on U.S. Senate contests. Each row corresponds to an individual candidate, keyed to the candidate\u2019s first Senate election used in the dataset, and includes (i) an election vote margin for that first contest and (ii) information on whether the individual later appeared as a director on the board of a publicly traded firm during the BoardEx coverage period.\n\nCorporate board service outcomes are based on BoardEx\u2019s historical database of publicly traded firm directorships, which compiles board membership information from public disclosures for firms traded on U.S. exchanges. The BoardEx coverage window used here spans 2000\u20132013. Election results used to construct the vote margin were drawn from official election returns and standard political data sources. The board-service outcome variables are constructed to exclude board positions held prior to the candidate\u2019s first Senate election. The dataset also applies eligibility restrictions consistent with the underlying data availability window (e.g., board outcomes are only observed in 2000\u20132013) and excludes cases where board service cannot be meaningfully assessed (such as candidates who did not survive into the relevant observation window or other similar sample restrictions implemented in the source study).\n","file_sha256":"7c30113ed34649d0517845d711f5fa66adbcc9ae997bc77780dcbada92691254","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":"7c30113ed34649d0517845d711f5fa66adbcc9ae997bc77780dcbada92691254","transforms":[],"url":"https://huggingface.co/datasets/syrgkanislab/CausalReasoningBenchmark/resolve/edd0fe1c1d1c5c0a4f0e3e67a50481ac679fb888/data/ds_0079/data/data.csv"}},"difficulty":"M","id":"crb_papers.q114","level":"T2","meta":{"agent_reach":{"blocked_by":["no_reference_path","no_tool:rdrobust_robust_bias_corrected","no_tool:fuzzy_rd"],"dtypes":{"ds_0079":{"d_board0":"int64","everwon":"int64"}},"named":{"outcome":["d_board0"],"treatment":["everwon"]},"reachable":false,"rule":"magi_bench.reach/1"},"answer_format":{"figure_transform":"identity","round_to":null,"unit_scale":1.0},"cluster":"ds_0079","crb":{"data_path":"data/ds_0079/data/data.csv","dataset_id":"ds_0079","gold":{"ci95":[-0.03665507940386209,0.6919657798441574],"ci_rule":"effect \u00b1 1.96\u00b7|standard_error| (evaluate_result.ci_bounds)","effect":0.3276553502201477,"standard_error":0.1858726681755152},"identification":{"causal_quantity":"CLATE","cutoff":0.0,"outcomes":["d_board0"],"running_variable":"margin","strategy":"Regression Discontinuity","treatments":["everwon"],"variant":"fuzzy"},"identification_strategy":"Regression Discontinuity"},"naive":{"dataset":"ds_0079","treatment":"everwon","y":"d_board0"},"native_id":"114","reference_path":{"calls":[],"needs":["no_tool:rdrobust_robust_bias_corrected","no_tool:fuzzy_rd"],"provenance":"none","quotes":{},"reference_datasets":[],"source_id":"crb_papers.q114.script"}},"question":"What is the effect of serving a Senate term on the probability of ever serving on a corporate board, for candidates whose service is determined by election outcomes?","requires":[],"runner":null,"sources":["crb_papers.q114.gold","crb_papers.q114.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"}