{"id":"W4318486538","doi":"10.32920/21977024.v1","title":"Who to inspect? Using employee complaint data to inform workplace inspections in Ontario","year":2023,"lang":"en","type":"preprint","venue":"","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Centennial College; Toronto Metropolitan University","funders":"","keywords":"Complaint; Enforcement; Christian ministry; Business; Accounting; Public relations; Operations management; Engineering; Political science; 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":[0.006572414,0.0001575702,0.0003223047,0.001919449,0.003015667,0.0028386,0.001139212,0.0006497118,0.001630171],"category_scores_gemma":[0.02736579,0.0003842078,0.0002279188,0.006673627,0.001846292,0.001122653,0.001575082,0.0007782484,0.000273282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0541837,"about_ca_system_score_gemma":0.07491743,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9880632,"about_ca_topic_score_gemma":0.9923881,"domain_scores_codex":[0.9931496,0.001260186,0.000554713,0.000631588,0.003297559,0.001106399],"domain_scores_gemma":[0.9536731,0.01117866,0.01186745,0.001956911,0.01883045,0.002493397],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001482285,0.0001154742,0.9022985,0.0003100744,0.0000521071,0.0003346114,0.03734044,0.0006497421,0.0008560001,0.002121859,0.0143189,0.04145398],"study_design_scores_gemma":[0.00001163099,0.00004311368,0.9454862,0.0001687031,0.00002890243,0.00004262082,0.02597158,0.00119779,0.0004622017,0.0002667236,0.02628449,0.00003608022],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634583,0.001114912,0.001564838,0.007577126,0.0000411766,0.0001743869,0.005168505,0.00005762307,0.02084301],"genre_scores_gemma":[0.9901205,0.0006686516,0.001343363,0.0005464964,0.0000152972,0.00006321667,0.001610355,0.00001954171,0.005612482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0541837,"threshold_uncertainty_score":0.3931322,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2770489717194408,"score_gpt":0.3412195929696208,"score_spread":0.06417062125018003,"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."}}