{"id":"W4407874572","doi":"10.1177/0261927x251318887","title":"Automating the Detection of Linguistic Intergroup Bias Through Computerized Language Analysis","year":2025,"lang":"en","type":"article","venue":"Journal of Language and Social Psychology","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Lexical analysis; Abstraction; Ingroups and outgroups; Coding (social sciences); Computer science; Outgroup; Natural language processing; Linguistics; Sentence; Psychology; Sentiment analysis; Linguistic analysis; Artificial intelligence; Cognitive psychology; Social psychology; Statistics; Mathematics; Epistemology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.007337403,0.001137244,0.0007509467,0.004539061,0.0008852923,0.002214944,0.001071938,0.0004696272,0.0070092],"category_scores_gemma":[0.03366303,0.0004762296,0.0005595213,0.002303062,0.0008967419,0.002580099,0.002644485,0.001427191,0.004507819],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001260979,"about_ca_system_score_gemma":0.00197339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002978194,"about_ca_topic_score_gemma":0.00442368,"domain_scores_codex":[0.992762,0.003545146,0.0007385847,0.001551327,0.00107011,0.0003327751],"domain_scores_gemma":[0.958949,0.02421385,0.003342,0.003656937,0.009360374,0.0004777907],"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":[0.0006197525,0.0004222104,0.04137943,0.001041025,0.000126482,0.0003764013,0.01162763,0.003174757,0.1653549,0.00431354,0.02194808,0.7496157],"study_design_scores_gemma":[0.0003860696,0.001112701,0.1491445,0.0004860252,0.000298556,0.001186347,0.01421333,0.4513549,0.2653354,0.03188844,0.08410909,0.000484693],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3688288,0.0001940503,0.5963469,0.0007872473,0.0002354478,0.00281062,0.00469652,0.01840764,0.007692799],"genre_scores_gemma":[0.4080305,0.00012024,0.5798413,0.0002883852,0.0000854275,0.002911971,0.004585232,0.001133666,0.003003308],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007337403,"threshold_uncertainty_score":0.03880435,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768414251105102,"score_gpt":0.3330358385620776,"score_spread":0.3153516960510265,"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."}}