{"id":"W4400063884","doi":"10.2139/ssrn.4870527","title":"Political Sentiment and Credit Ratings","year":2024,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Credit Risk and Financial Regulations","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Politics; Sentiment analysis; Credit rating; Political science; Psychology; Business; Financial system; Natural language processing; Computer science; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001018033,0.0001014224,0.000200163,0.0004784331,0.0003556259,0.002286902,0.0001290952,0.0008707531,0.01462201],"category_scores_gemma":[0.01401994,0.000113311,0.0001473858,0.0008155237,0.0003387005,0.0006235865,0.0003256267,0.001159871,0.002472103],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004520855,"about_ca_system_score_gemma":0.0001999683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003153389,"about_ca_topic_score_gemma":0.00548287,"domain_scores_codex":[0.9995741,0.0001811623,0.00002638085,0.00004952678,0.00008203098,0.00008682362],"domain_scores_gemma":[0.9847401,0.004864261,0.006868459,0.0004172909,0.001245565,0.001864353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009968198,0.0004425948,0.9226215,0.00006289488,0.0001193002,0.0002801905,0.0008574509,0.001318544,0.0009668469,0.01680321,0.01890182,0.03662872],"study_design_scores_gemma":[0.00003758073,0.0001042132,0.9826066,0.00002628978,0.00004013517,0.0001337011,0.000554517,0.002792944,0.000176166,0.00742476,0.006084277,0.00001886086],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9373232,0.0009032284,0.0004839869,0.004300384,0.00009241254,0.00001363011,0.0007868911,0.00002587295,0.05607037],"genre_scores_gemma":[0.9950965,0.0001666044,0.00003645996,0.0001319661,0.000106086,0.000002961968,0.000194113,0.000005485576,0.004259867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01462201,"threshold_uncertainty_score":0.04891545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01089087738243009,"score_gpt":0.2261893504973811,"score_spread":0.215298473114951,"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."}}