{"id":"W4408498938","doi":"10.1080/10345329.2025.2466869","title":"Detecting, disrupting and deterring sexual exploitation of trafficked persons: leveraging beneficial ownership registries to reduce criminogenic information asymmetry and raise public expectations","year":2025,"lang":"en","type":"article","venue":"Current Issues in Criminal Justice","topic":"Sex work and related issues","field":"Social Sciences","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"","keywords":"Information asymmetry; Business; Public ownership; Public relations; Computer security; Internet privacy; Public economics; Economics; Computer science; Finance; Political science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008955754,0.0002698458,0.000260829,0.002297125,0.001982597,0.005322536,0.001078586,0.001662145,0.003368706],"category_scores_gemma":[0.02859323,0.0002825171,0.0003545746,0.0008269811,0.00439591,0.006332119,0.005303563,0.001479669,0.000757337],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122129,"about_ca_system_score_gemma":0.00546664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004551544,"about_ca_topic_score_gemma":0.008416037,"domain_scores_codex":[0.9944921,0.002807031,0.0002306341,0.0004049946,0.001441532,0.0006238776],"domain_scores_gemma":[0.9829496,0.009649524,0.003838067,0.001575959,0.001426428,0.0005604072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001465919,0.001021923,0.09070974,0.0005631753,0.00004946222,0.0007483372,0.01443927,0.002392469,0.006336103,0.2118858,0.01179137,0.6599158],"study_design_scores_gemma":[0.0001502925,0.002484047,0.1443216,0.005198696,0.0004258282,0.004181882,0.06153752,0.03176333,0.04743624,0.337363,0.3647969,0.0003406947],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5902678,0.004793783,0.1039564,0.05654757,0.0003034179,0.0009803858,0.0003495918,0.0005272251,0.2422738],"genre_scores_gemma":[0.9748142,0.002255718,0.01617473,0.00204227,0.00008686422,0.0001202215,0.00008955631,0.00002436243,0.004392053],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008955754,"threshold_uncertainty_score":0.04736316,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08533502835173225,"score_gpt":0.3851828334491108,"score_spread":0.2998478050973786,"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."}}