{"id":"W4412166017","doi":"10.1017/psrm.2025.10032","title":"Legislative reciprocity: Using a proposal lottery to identify causal effects","year":2025,"lang":"en","type":"article","venue":"Political Science Research and Methods","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"University of Cambridge","keywords":"Lottery; Legislature; Reciprocity (cultural anthropology); Economics; Public economics; Political science; Microeconomics; Psychology; Social psychology; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","sts"],"consensus_categories":["sts"],"category_scores_codex":[0.01701452,0.00009711093,0.0002073309,0.0004201269,0.001676834,0.0004753149,0.0003243301,0.0000963665,0.0000202086],"category_scores_gemma":[0.01721892,0.00008037396,0.00003104014,0.002538805,0.003222728,0.0003925215,0.0002653381,0.0003236436,0.00002000905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007291643,"about_ca_system_score_gemma":0.002178299,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03485903,"about_ca_topic_score_gemma":0.001143067,"domain_scores_codex":[0.9936213,0.002402028,0.0002230396,0.0004652381,0.0009945681,0.002293793],"domain_scores_gemma":[0.9952013,0.002494288,0.00001832792,0.0001769703,0.0006125621,0.00149657],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000125498,0.00003617584,0.003663572,0.00003945313,0.000004556612,0.000002888963,0.00097431,2.365465e-7,0.03382693,0.9523159,0.00007906453,0.009044331],"study_design_scores_gemma":[0.0002448714,0.0004122,0.06135033,0.0002703004,0.00001850926,0.000002064081,0.001228789,0.0006713608,0.04662671,0.8783551,0.01054571,0.0002740843],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8103205,0.0001015626,0.0752427,0.02365827,0.0006649466,0.001504527,0.000004005189,0.00007787242,0.08842561],"genre_scores_gemma":[0.9696912,0.000001715687,0.02815701,0.0003883373,0.0002681054,0.00005700609,2.188021e-7,0.00000486139,0.001431601],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1593706,"threshold_uncertainty_score":0.9996228,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2476513732363438,"score_gpt":0.6410554643837668,"score_spread":0.393404091147423,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}