{"id":"W3030280736","doi":"10.3138/cpp.2018-065","title":"Who to Inspect? Using Employee Complaint Data to Inform Workplace Inspections in Ontario","year":2020,"lang":"en","type":"article","venue":"Canadian Public Policy","topic":"Regulation and Compliance Studies","field":"Business, Management and Accounting","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University; Centennial College; Toronto Metropolitan University","funders":"","keywords":"Complaint; Christian ministry; Enforcement; Business; Public relations; Accounting; Political science; Law","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0001186931,0.0001767591,0.0002235942,0.001184278,0.0004490134,0.0006449826,0.000704613,0.00004447097,0.0003269165],"category_scores_gemma":[0.0003907983,0.0001997385,0.0000256714,0.003202867,0.00003556267,0.001277411,0.0005074941,0.0001818129,0.0006058451],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001184323,"about_ca_system_score_gemma":0.001410735,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9311761,"about_ca_topic_score_gemma":0.9974388,"domain_scores_codex":[0.9985785,0.000005166679,0.0002744776,0.0003713979,0.0001759333,0.0005945645],"domain_scores_gemma":[0.9990494,0.000009735097,0.00005705209,0.0004798574,0.0001203511,0.0002836206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002243894,0.00002287153,0.502108,0.00004555878,0.000052571,0.0000275768,0.002052189,0.001485738,0.0000150059,0.2305641,0.2576984,0.005905606],"study_design_scores_gemma":[0.0001392091,0.000004660001,0.3946059,0.00001965964,0.00000392768,0.000001097629,0.0002040613,0.001390281,1.854038e-7,0.0001955615,0.6032675,0.0001679723],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.560926,0.00001985401,0.0004529023,0.2704119,0.0003347289,0.000763039,0.00005339454,0.0001834702,0.1668547],"genre_scores_gemma":[0.9375888,5.942026e-7,0.0002614127,0.06036226,0.0009969135,0.00001623107,0.00005885335,0.00002251449,0.0006924164],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3766628,"threshold_uncertainty_score":0.8145099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.185560309610158,"score_gpt":0.2996914119616924,"score_spread":0.1141311023515344,"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."}}