{"id":"W3190412713","doi":"10.1111/ssqu.13036","title":"Voters’ view of leaders during the Covid‐19 crisis: Quantitative analysis of keyword descriptions provides strength and direction of evaluations","year":2021,"lang":"en","type":"article","venue":"Social Science Quarterly","topic":"Electoral Systems and Political Participation","field":"Social Sciences","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Vetenskapsrådet; Université de Montréal; King's College London; University of Toronto; Universität Wien; Universitat Pompeu Fabra; Karlstads universitet; University College Dublin; Helsingin Yliopisto","keywords":"Polarization (electrochemistry); Descriptive statistics; Sentiment analysis; Psychology; Coronavirus disease 2019 (COVID-19); Pandemic; Regression analysis; Measure (data warehouse); Social psychology; Political science; Econometrics; Computer science; Economics; Statistics; Natural language processing; Data mining; Mathematics; Medicine; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004997045,0.0001711451,0.0002471379,0.00232694,0.0005305763,0.001737688,0.0001745588,0.0004178119,0.00128226],"category_scores_gemma":[0.0311247,0.0001104278,0.0002622918,0.001553316,0.0007038071,0.001579569,0.001002662,0.0005021641,0.0003713846],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005619807,"about_ca_system_score_gemma":0.0003190816,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008111598,"about_ca_topic_score_gemma":0.001499573,"domain_scores_codex":[0.9960262,0.002305029,0.0004729932,0.0002470747,0.000775289,0.0001733692],"domain_scores_gemma":[0.9703572,0.01648408,0.007126278,0.0009529876,0.004433747,0.0006457056],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001592569,0.0001165251,0.8663016,0.0006731226,0.0002050935,0.0001787042,0.04576441,0.0007098439,0.01613896,0.002670982,0.001466205,0.06418192],"study_design_scores_gemma":[0.00003673827,0.0005240493,0.9149788,0.0001344966,0.0001099919,0.000251214,0.06806947,0.003109429,0.005656226,0.002018965,0.005006622,0.0001040444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946775,0.00007463001,0.001324066,0.0001186784,0.00001361033,0.00002902164,0.0002937129,0.00001007175,0.003458632],"genre_scores_gemma":[0.9989108,0.00003539661,0.0005433285,0.00002161351,0.000009409987,0.00002820643,0.0002268941,0.000005073259,0.0002193346],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004997045,"threshold_uncertainty_score":0.02642721,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1093158721498611,"score_gpt":0.4307858213620254,"score_spread":0.3214699492121643,"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."}}