{"id":"W2904574542","doi":"10.7202/1057109ar","title":"Beyond Face Value: A Policy Analysis of Employment Equity Programs and Reporting in Ontario Public Colleges","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Higher Education","topic":"Higher Education Research Studies","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Mandate; Equity (law); Diversity (politics); Public relations; Political science; Public policy; Higher education; Face (sociological concept); Public administration; The arts; Value (mathematics); Economic growth; Sociology; Economics; Social science","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001959929,0.00008082811,0.0003254122,0.001410802,0.00017679,0.0001425009,0.0002156591,0.00006024443,0.0004983532],"category_scores_gemma":[0.0005251007,0.00007815646,0.00008782477,0.001858806,0.0001873165,0.0002940069,0.00002160587,0.000191294,0.000002200716],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002215495,"about_ca_system_score_gemma":0.02631696,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8177552,"about_ca_topic_score_gemma":0.9648989,"domain_scores_codex":[0.9980989,0.000192368,0.0007658985,0.0001421663,0.00042595,0.000374772],"domain_scores_gemma":[0.9976423,0.00007887894,0.00102229,0.000143418,0.0005767631,0.0005362938],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000002237843,0.00006865295,0.9590902,0.000008089855,0.0001621894,0.000001791568,0.02706194,0.00001268709,0.00001380714,0.01039803,0.001488263,0.00169213],"study_design_scores_gemma":[0.00009234004,0.00004500142,0.8908103,0.00003331056,0.00006249391,0.000001243161,0.007672088,7.37185e-7,0.000005307865,0.0008645596,0.1003452,0.00006740975],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.968491,0.0009512469,0.000001047895,0.01841089,0.0005367433,0.0002685544,0.000001835427,0.000002560234,0.01133618],"genre_scores_gemma":[0.9817056,0.00002245481,0.0001859806,0.0001537751,0.000117355,0.00001205453,0.000005178812,0.000005404558,0.01779218],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1471437,"threshold_uncertainty_score":0.9792029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09791806750703926,"score_gpt":0.4283793590381275,"score_spread":0.3304612915310883,"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."}}