{"id":"W2911580435","doi":"10.1111/capa.12309","title":"Why electoral reform might improve representation and why it might make it worse","year":2019,"lang":"en","type":"article","venue":"Canadian Public Administration","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Representation (politics); Parliament; Proportional representation; Congruence (geometry); Ideology; Preference; Government (linguistics); Electoral system; Political science; Public economics; Political economy; Public administration; Economics; Microeconomics; Politics; Social psychology; Law; Psychology; Democracy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004628713,0.0001300821,0.0001548535,0.0001537901,0.0004189415,0.000449409,0.0001332085,0.0002070655,0.001041126],"category_scores_gemma":[0.0002368546,0.0001312495,0.00004575562,0.0004031021,0.0001145063,0.0006864307,0.000008767764,0.0001364486,0.0001174076],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007246083,"about_ca_system_score_gemma":0.00142434,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.3047709,"about_ca_topic_score_gemma":0.9766072,"domain_scores_codex":[0.9982337,0.0001797074,0.000319564,0.000330555,0.0003212462,0.0006152689],"domain_scores_gemma":[0.9985507,0.0000572787,0.0001171687,0.0002180772,0.0002124786,0.0008442986],"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":[0.00004090536,0.00006158041,0.05906326,0.00006435606,0.00004675369,0.00002125534,0.002099958,4.070089e-7,0.00104902,0.803991,0.1293423,0.004219226],"study_design_scores_gemma":[0.0002377405,0.0001798787,0.005656112,0.0000179634,0.00001471023,0.000003996779,0.0009419961,0.0001753624,0.0002798041,0.001532937,0.9907175,0.0002419441],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5521739,0.00004627111,0.00008804533,0.3873804,0.0009435573,0.0009263455,0.00005012305,0.00006752829,0.05832389],"genre_scores_gemma":[0.986052,0.000003094875,0.00003818109,0.005005982,0.0004438732,0.00004429294,0.0001314295,0.00001308389,0.008267999],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8613752,"threshold_uncertainty_score":0.999872,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04114805335054927,"score_gpt":0.3304373221604134,"score_spread":0.2892892688098642,"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."}}