{"id":"W2598454312","doi":"10.1007/978-3-319-49442-5_6","title":"Mixed-Strategy Kant-Nash Equilibrium and Private Contributions to a Public Good","year":2017,"lang":"en","type":"book-chapter","venue":"","topic":"Fiscal Policy and Economic Growth","field":"Economics, Econometrics and Finance","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"","keywords":"Public good; Nash equilibrium; Per capita; Phenomenon; Economics; Simple (philosophy); Aggregate (composite); Private good; Population; Per capita income; Mathematical economics; Microeconomics; Positive economics; Public economics; Sociology; Epistemology; Demography; Philosophy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002429474,0.001466711,0.001089827,0.0009197719,0.001333197,0.004692581,0.001846512,0.004130316,0.01709933],"category_scores_gemma":[0.007516762,0.0005664431,0.0009059677,0.001426278,0.003931796,0.004729888,0.002522534,0.003223174,0.002018492],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004031344,"about_ca_system_score_gemma":0.002989095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002659761,"about_ca_topic_score_gemma":0.003619416,"domain_scores_codex":[0.9986175,0.0007838166,0.00004272286,0.0001144501,0.0002758959,0.0001654904],"domain_scores_gemma":[0.9978443,0.001442702,0.0001225856,0.0001862434,0.0002305979,0.0001734318],"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":[0.0000201608,0.00001550933,0.00002960465,0.00002745039,0.00000982749,0.00001858271,0.00004296825,0.01085884,0.00009989465,0.9836152,0.002206883,0.003055139],"study_design_scores_gemma":[0.000009418494,0.000002289777,0.00001265192,0.00001193843,0.000002395584,0.000007052821,0.00001684595,0.01211113,0.00003899013,0.9865442,0.001239591,0.000003584697],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05910053,0.00290778,0.4701335,0.01308788,0.0005820777,0.0001237704,0.000431926,0.000312417,0.4533202],"genre_scores_gemma":[0.8202599,0.002641896,0.04819144,0.0009116539,0.0004451845,0.0003416781,0.0001466757,0.0001841363,0.1268774],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01709933,"threshold_uncertainty_score":0.05720294,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06573736786613289,"score_gpt":0.2456135815142881,"score_spread":0.1798762136481552,"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."}}