{"id":"W3037341367","doi":"10.1017/psrm.2020.25","title":"Do natural disasters help the environment? How voters respond and what that means","year":2020,"lang":"en","type":"article","venue":"Political Science Research and Methods","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":113,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Natural disaster; Voting; Referendum; Climate change; Flooding (psychology); Flood myth; Exploit; Extreme weather; Affect (linguistics); Political science; Geospatial analysis; Politics; Public economics; Economics; Geography; Psychology; Computer security; Computer science; Ecology","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":["sts","scholarly_communication"],"consensus_categories":["sts"],"category_scores_codex":[0.009479968,0.00009586483,0.0001437572,0.00006674754,0.00144977,0.00175736,0.000360691,0.00005955994,0.00003792651],"category_scores_gemma":[0.004144168,0.00005948293,0.00002990361,0.0005365626,0.00713171,0.001131052,0.0002282432,0.000362121,0.00001005226],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001569641,"about_ca_system_score_gemma":0.0001852589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00201155,"about_ca_topic_score_gemma":0.0001335223,"domain_scores_codex":[0.9946117,0.002047898,0.0001157528,0.0004116017,0.001161719,0.001651264],"domain_scores_gemma":[0.9958672,0.002163511,0.00002090182,0.0001545289,0.00007833029,0.001715549],"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":[0.00002547654,0.00001493661,0.002822528,0.00001836097,0.000005183998,0.000002682195,0.007283951,2.121784e-7,0.009275303,0.937318,0.00009985459,0.04313346],"study_design_scores_gemma":[0.001112878,0.001809351,0.08492684,0.0002226683,0.00005761234,0.00001354564,0.2478613,0.004638193,0.03939988,0.3608686,0.2579263,0.001162832],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6311852,0.001077909,0.001590478,0.3626301,0.0002018692,0.0005261695,0.000004613877,0.00002770982,0.002755914],"genre_scores_gemma":[0.9971041,0.0001353423,0.001345578,0.0007884304,0.0002349496,0.00001929431,4.293428e-7,0.000005297227,0.0003665743],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5764495,"threshold_uncertainty_score":0.9998502,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2407195265323983,"score_gpt":0.5179058000293262,"score_spread":0.2771862734969279,"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."}}