{"id":"W3144256111","doi":"10.2139/ssrn.3714453","title":"Elections, Political Polarization, and Economic Uncertainty","year":2020,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Market Dynamics and Volatility","field":"Economics, Econometrics and Finance","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Polarization (electrochemistry); Presidential system; Presidential election; Download; Politics; Political science; National election; Developing country; Economics; Development economics; Demographic economics; Political economy; Economic policy; Economic growth; Law","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008781998,0.0001160288,0.0002270611,0.00008067515,0.0001939394,0.00009689264,0.0001370672,0.00007613217,0.0001790903],"category_scores_gemma":[0.0001319221,0.0001326417,0.00007627223,0.00009852887,0.0000430431,0.0001795414,0.00003483809,0.0008325821,0.00005380386],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006794955,"about_ca_system_score_gemma":0.0003970915,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003950956,"about_ca_topic_score_gemma":0.000394986,"domain_scores_codex":[0.9980305,0.00002457462,0.0004278076,0.0002673481,0.00002391867,0.001225876],"domain_scores_gemma":[0.9994838,0.00002974948,0.0001610534,0.00009992966,0.00002098252,0.0002044673],"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":[0.0000162426,0.0000104112,0.2001622,0.000003414293,0.00004602764,2.820887e-7,0.00002763424,0.0000122161,0.000004134991,0.7991826,0.00005196755,0.0004829016],"study_design_scores_gemma":[0.0004750022,0.0001635298,0.01440947,0.000001927994,0.000008149723,0.00007633508,0.0001882785,0.06414577,0.000001628321,0.9094012,0.01093408,0.0001946759],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.897677,0.004353379,0.05932021,0.02316924,0.0003461713,0.0002056268,0.0001005465,0.00006461021,0.01476322],"genre_scores_gemma":[0.9978828,0.0007214294,0.00007757916,0.0006023032,0.0002813182,0.000002033897,0.000008205834,0.00001676207,0.0004076097],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1857527,"threshold_uncertainty_score":0.5408971,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01146145407422836,"score_gpt":0.2121759420679191,"score_spread":0.2007144879936908,"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."}}