{"id":"W3122437394","doi":"","title":"Decentralization and electoral swings","year":2018,"lang":"en","type":"preprint","venue":"Digital Archive @ GSU","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Universidade de Vigo; Ministerio de Ciencia e Innovación; United Nations Development Programme; United States Agency for International Development","keywords":"Decentralization; Panel data; Recession; Government (linguistics); Politics; Economics; Political science; Economic policy; Electoral geography; Economic system; Development economics; Macroeconomics; Market economy","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":[0.001901595,0.0001247058,0.0007623872,0.001831053,0.0007838405,0.001337044,0.0003973712,0.0002780988,0.007818589],"category_scores_gemma":[0.01265796,0.0002216933,0.0003294045,0.002583719,0.001095387,0.0008636955,0.002136228,0.0007194483,0.0006775121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007075482,"about_ca_system_score_gemma":0.0003205317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00395876,"about_ca_topic_score_gemma":0.005412519,"domain_scores_codex":[0.9983723,0.0004633217,0.0001355228,0.0004334826,0.0001603856,0.0004350143],"domain_scores_gemma":[0.9871737,0.003892086,0.005307034,0.001570833,0.0008345915,0.001221837],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000665511,0.0001126064,0.9681066,0.00007154337,0.0001686554,0.00009581828,0.002035121,0.003720969,0.001439206,0.006191764,0.0005078667,0.01688423],"study_design_scores_gemma":[0.00001838142,0.00007230611,0.9946786,0.000009147546,0.00001765583,0.00005015002,0.0005747859,0.001315704,0.0002588255,0.001924262,0.001071635,0.000008554804],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996042,0.0001151722,0.0005868602,0.00009628049,0.000004127057,0.000009750887,0.0003052411,0.00001350115,0.002827037],"genre_scores_gemma":[0.9993149,0.0000173299,0.00007576669,0.000006456206,0.000006547952,0.000003590076,0.0002317309,0.000003190049,0.0003405176],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007818589,"threshold_uncertainty_score":0.02615577,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03548706354603939,"score_gpt":0.3344443519417198,"score_spread":0.2989572883956805,"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."}}