{"id":"W4235636304","doi":"10.32920/ryerson.14636976","title":"Human trafficking and media myths: federal funding, communication strategies, and Canadian anti-trafficking programs","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Sex work and related issues","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; York University","funders":"Creations of Advanced Catalytic Transformation for the Sustainable Manufacturing at Low Energy, Low Environmental Load; Australian Government","keywords":"Emotive; Mythology; Narrative; Government (linguistics); Politics; Political science; Public relations; Bureaucracy; Human trafficking; Public administration; Sociology; Media studies; Criminology; Law","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":[0.005971071,0.0003935927,0.0002303663,0.004828883,0.0250193,0.01139176,0.001432074,0.002373377,0.007700554],"category_scores_gemma":[0.01609586,0.0003091841,0.0001859392,0.005069634,0.0219018,0.004459342,0.005538536,0.003023283,0.0002146627],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.07883389,"about_ca_system_score_gemma":0.06964227,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9480656,"about_ca_topic_score_gemma":0.9494439,"domain_scores_codex":[0.9962788,0.001067935,0.00007060389,0.0002459575,0.001270566,0.001066155],"domain_scores_gemma":[0.9906694,0.005757663,0.0006806942,0.0002793982,0.001808884,0.0008039664],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00006031837,0.00003748451,0.006614712,0.0001674252,0.00001019819,0.0003681687,0.5838997,0.0001980986,0.0006270189,0.345453,0.01267743,0.04988644],"study_design_scores_gemma":[0.0000131657,0.00002477162,0.0182771,0.0006815358,0.0000348945,0.0001463686,0.6460627,0.0004811821,0.0009509568,0.01975369,0.3134872,0.00008657995],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5152921,0.006241674,0.001478158,0.1152689,0.0003954962,0.0000577027,0.0003103258,0.00007109585,0.3608846],"genre_scores_gemma":[0.9851554,0.002175502,0.0003747322,0.00173568,0.00004767521,0.00002417521,0.00003353791,0.0000203824,0.01043298],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9211661,"threshold_uncertainty_score":0.5719826,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04910590854142682,"score_gpt":0.3246490595386795,"score_spread":0.2755431509972527,"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."}}