{"id":"W4410387207","doi":"10.59297/vg1gcm05","title":"Social Media Use by Canadian Law Enforcement Agencies","year":2025,"lang":"en","type":"article","venue":"Proceedings of the ... International ISCRAM Conference","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University of Edmonton","funders":"","keywords":"Law enforcement; Social media; Law; Enforcement; Political science; Criminology; Sociology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001643994,0.0001077574,0.0001014749,0.0001088692,0.0002117064,0.0004374854,0.00157454,0.00006139774,0.00005200976],"category_scores_gemma":[0.0001518532,0.00008823545,0.00006656005,0.0002385708,0.0001028765,0.0005785933,0.0002987029,0.0001378002,0.0000104937],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000188127,"about_ca_system_score_gemma":0.0002130255,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.023228,"about_ca_topic_score_gemma":0.007738192,"domain_scores_codex":[0.9989891,0.000004557744,0.0002048144,0.0002236149,0.000376558,0.0002013498],"domain_scores_gemma":[0.9991553,0.0000397511,0.0001168342,0.0000918764,0.0005359255,0.00006035198],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000004236311,0.00001069303,0.0003006921,0.000006070691,0.00002951638,2.034569e-7,0.0006877918,0.000001274301,0.008781967,0.9695604,0.0184765,0.002140651],"study_design_scores_gemma":[0.0007554683,0.00005492572,0.003465783,0.000266523,0.00003831496,0.00001037188,0.001002191,0.01328359,0.3509697,0.1321159,0.4975016,0.0005357403],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.2059969,0.00004212632,0.006108699,0.01676396,0.003061619,0.0004327194,0.00007062332,0.0001851808,0.7673382],"genre_scores_gemma":[0.9939221,0.000009534934,0.0008539886,0.0008713187,0.00004360936,0.00001476677,0.000003344328,0.000003584871,0.004277736],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8374445,"threshold_uncertainty_score":0.9832764,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02252407049841617,"score_gpt":0.2362148564953701,"score_spread":0.2136907859969539,"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."}}