{"id":"W1571632442","doi":"10.2139/ssrn.1026925","title":"Ideology Classifiers for Political Speech","year":2007,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Media Influence and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Kellogg's (Canada)","funders":"","keywords":"Ideology; Politics; Linguistics; Political science; Speech recognition; Sociology; Computer science; Law; Philosophy","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":[0.005449937,0.00132487,0.001646106,0.006522932,0.002085326,0.00309325,0.001510831,0.002898762,0.01019793],"category_scores_gemma":[0.01563767,0.0005623241,0.001654608,0.001728547,0.0006584043,0.003137879,0.001683395,0.003515076,0.008746666],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001362288,"about_ca_system_score_gemma":0.001965633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002063538,"about_ca_topic_score_gemma":0.003702849,"domain_scores_codex":[0.9965369,0.0009206983,0.0002798136,0.0007801006,0.0008865423,0.0005960481],"domain_scores_gemma":[0.9882813,0.007641012,0.0006577234,0.001065513,0.001730117,0.0006242954],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001865373,0.000979741,0.03185641,0.0003493735,0.0003856521,0.0001993638,0.0002555655,0.0213505,0.007276797,0.01329046,0.07380357,0.8483871],"study_design_scores_gemma":[0.000200745,0.0003265393,0.01126325,0.000203295,0.0002416913,0.0002572109,0.0004364429,0.9138284,0.01368081,0.04545431,0.01403375,0.00007354085],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4358428,0.009059216,0.4611585,0.007102868,0.002874385,0.0009240172,0.02116171,0.01485197,0.04702455],"genre_scores_gemma":[0.8726906,0.0009156918,0.08612281,0.0005120542,0.002528931,0.0005597541,0.02122691,0.0004171646,0.01502616],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01019793,"threshold_uncertainty_score":0.03411549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02556849753778421,"score_gpt":0.3655900343524092,"score_spread":0.340021536814625,"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."}}