{"id":"W2344152004","doi":"10.1017/s0008423916000056","title":"Partisans without Parties: Party Systems as Partisan Inhibitors?","year":2016,"lang":"en","type":"article","venue":"Canadian Journal of Political Science","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Wilfrid Laurier University","funders":"","keywords":"Identification (biology); Politics; Context (archaeology); Political science; Similarity (geometry); Raising (metalworking); Work (physics); Test (biology); Mechanism (biology); Third party; Public administration; Law; Computer science; Geography; Engineering; Internet privacy","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004970565,0.0002881838,0.0008581223,0.002412161,0.003410088,0.004388485,0.001248959,0.0004053079,0.01334588],"category_scores_gemma":[0.0239953,0.0002391826,0.0006054764,0.004250026,0.002690789,0.001245538,0.002253508,0.001079949,0.0006397387],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005147669,"about_ca_system_score_gemma":0.005617343,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5259197,"about_ca_topic_score_gemma":0.5433694,"domain_scores_codex":[0.9949226,0.00130417,0.0002215299,0.0007986897,0.001287639,0.001465288],"domain_scores_gemma":[0.9785956,0.008484709,0.005765408,0.002503333,0.002252672,0.002398368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003866414,0.00005375646,0.9673997,0.0001037896,0.000214683,0.00007477723,0.002914349,0.0008257385,0.000508171,0.0117183,0.001626101,0.0141741],"study_design_scores_gemma":[0.00003139129,0.0000389251,0.97938,0.00003781056,0.0001341216,0.00004423471,0.003728204,0.002725909,0.0003467663,0.004091017,0.009422458,0.00001917217],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9552755,0.0005209132,0.003140192,0.0009996664,0.00002962029,0.0001025234,0.002316584,0.00004968141,0.03756526],"genre_scores_gemma":[0.9984574,0.00004372165,0.0001843348,0.00003074625,0.00001005313,0.00001082286,0.0004196798,0.000007583994,0.0008357253],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4740803,"threshold_uncertainty_score":0.9537444,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0404441081426208,"score_gpt":0.3393312576339537,"score_spread":0.2988871494913329,"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."}}