{"id":"W4404579927","doi":"10.1016/j.cognition.2024.106012","title":"Partisan language in a polarized world: In-group language provides reputational benefits to speakers while polarizing audiences","year":2024,"lang":"en","type":"article","venue":"Cognition","topic":"Social Media and Politics","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Psychology; Linguistics; Group (periodic table); Chemistry","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":[0.002058664,0.0003027251,0.0003890672,0.0008708241,0.002153964,0.007347065,0.0004241034,0.00164503,0.009981987],"category_scores_gemma":[0.01304265,0.0004077224,0.0002721167,0.0006242248,0.002598314,0.003834255,0.002985077,0.001784451,0.0009509623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006376347,"about_ca_system_score_gemma":0.0006096282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002005165,"about_ca_topic_score_gemma":0.002481848,"domain_scores_codex":[0.998246,0.0006962704,0.00003611567,0.0003442199,0.0003205843,0.0003569459],"domain_scores_gemma":[0.9893992,0.003230837,0.002625559,0.001185442,0.0009474695,0.00261154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004642309,0.002585058,0.4897202,0.0004337403,0.0006289298,0.002665533,0.09276365,0.003628818,0.1648112,0.1285256,0.009684057,0.09991094],"study_design_scores_gemma":[0.0002744517,0.0009058146,0.7867383,0.00009767277,0.0005118687,0.001082149,0.04713675,0.00888995,0.009688061,0.1332184,0.01122241,0.0002342444],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9630533,0.00006081696,0.001484377,0.001026838,0.00003308008,0.000005485603,0.00002948664,0.00001925596,0.03428739],"genre_scores_gemma":[0.9986542,0.00002244203,0.0002811279,0.0001763251,0.00002478974,0.000002961596,0.00002086178,0.00002762619,0.0007894898],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009981987,"threshold_uncertainty_score":0.03339309,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03139944475466769,"score_gpt":0.340048981534432,"score_spread":0.3086495367797644,"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."}}