{"id":"W1987084050","doi":"10.1177/1354068814560933","title":"Voting correctly in lab elections with monetary incentives","year":2014,"lang":"en","type":"article","venue":"Party Politics","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Incentive; Voting; Context (archaeology); Bullet voting; Contingent vote; Order (exchange); Microeconomics; Distribution (mathematics); Cardinal voting systems; Ranked voting system; Economics; Single-member district; Politics; Affect (linguistics); Political science; Group voting ticket; Law; Psychology; Mathematics; Finance","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":[0.008001273,0.0003302292,0.001015506,0.0008356689,0.0007072529,0.002498088,0.0004054594,0.0008740966,0.009105661],"category_scores_gemma":[0.05114517,0.0003267465,0.0003595193,0.0007626725,0.001185228,0.002403254,0.001516474,0.0009952741,0.001803037],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003645715,"about_ca_system_score_gemma":0.0003575622,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005696272,"about_ca_topic_score_gemma":0.0008317663,"domain_scores_codex":[0.992317,0.005202027,0.0003948374,0.0005594559,0.0004871942,0.00103942],"domain_scores_gemma":[0.9494216,0.03166253,0.01034281,0.005792582,0.001080121,0.001700397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.01808377,0.003028377,0.5929151,0.0007124544,0.0008912248,0.0008333122,0.005852924,0.06334408,0.01533568,0.07767069,0.008739606,0.2125927],"study_design_scores_gemma":[0.001336451,0.004474348,0.6023467,0.0002299346,0.0002927921,0.0008400175,0.006725801,0.1620355,0.01214911,0.1911787,0.01807701,0.0003136564],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.98587,0.00007136643,0.002416905,0.0002743219,0.00001785999,0.00002849477,0.0001250611,0.00001963603,0.01117636],"genre_scores_gemma":[0.998521,0.0000293813,0.0004185516,0.00004954396,0.00002331834,0.00002655288,0.000117603,0.000006520314,0.0008075329],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009105661,"threshold_uncertainty_score":0.04231524,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02920237958752026,"score_gpt":0.3164160888036169,"score_spread":0.2872137092160966,"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."}}