{"id":"W2116188555","doi":"10.1016/j.jet.2014.03.004","title":"School choice with controlled choice constraints: Hard bounds versus soft bounds","year":2014,"lang":"en","type":"article","venue":"Journal of Economic Theory","topic":"Game Theory and Voting Systems","field":"Economics, Econometrics and Finance","cited_by":286,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal","funders":"","keywords":"School choice; Diversity (politics); Pareto optimal; Type (biology); Computer science; Pareto principle; Mathematical optimization; Selection (genetic algorithm); Upper and lower bounds; Control (management); Scheme (mathematics); Mathematical economics; Mathematics; Economics; Multi-objective optimization; Artificial intelligence; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.006551881,0.0003318215,0.001427075,0.0003936661,0.0002037481,0.0003158974,0.000635442,0.0001792271,0.002020154],"category_scores_gemma":[0.00203645,0.000304375,0.0004220913,0.00008810471,0.0003943895,0.0006565438,0.0000434409,0.0005292324,0.00104518],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003862344,"about_ca_system_score_gemma":0.000174938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000363648,"about_ca_topic_score_gemma":0.00002914252,"domain_scores_codex":[0.9970981,0.000236196,0.001744003,0.0003817127,0.00005852503,0.0004814885],"domain_scores_gemma":[0.9942955,0.002176055,0.002621135,0.0004919064,0.0000893051,0.0003260423],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003638975,0.0001320399,0.03395423,0.00005106053,0.001254141,0.000007885439,0.0002930535,0.001021974,0.00006334919,0.956398,0.001671797,0.001513572],"study_design_scores_gemma":[0.1116191,0.004276902,0.02922917,0.0005727636,0.0004680815,0.0006154448,0.001524757,0.002897929,0.0001809735,0.4049088,0.4412734,0.002432624],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8847888,0.001454796,0.008404341,0.0005002209,0.004478575,0.000328509,0.00005320519,0.00005091887,0.09994061],"genre_scores_gemma":[0.9938461,0.00003007241,0.0003109143,0.0003620646,0.001956688,0.00001092665,0.00000264952,0.00005741992,0.003423151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5514891,"threshold_uncertainty_score":0.9999408,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0242208678987575,"score_gpt":0.2358945501793012,"score_spread":0.2116736822805438,"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."}}