{"id":"W34918129","doi":"10.1093/mr/roab068","title":"Visible Minority Work Experiences in Canadian IT/ICT Sectors","year":2009,"lang":"en","type":"article","venue":"Americas Conference on Information Systems","topic":"Gender Diversity and Inequality","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Information and Communications Technology; Workforce; Economic shortage; Government (linguistics); Business; Government sector; Perception; Work (physics); Diversity (politics); Public relations; Business sector; Economic growth; Political science; Engineering; Private sector; Psychology; Economics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007605075,0.0001057086,0.0001791611,0.0002604488,0.0003928918,0.0003249031,0.0003001274,0.00009961367,0.0002617359],"category_scores_gemma":[0.0001255074,0.000106928,0.00003571534,0.0007375221,0.000122025,0.001290762,0.000009873083,0.000128932,0.0004119634],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003306868,"about_ca_system_score_gemma":0.0006221114,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6637464,"about_ca_topic_score_gemma":0.09235986,"domain_scores_codex":[0.9984561,0.0002116334,0.0003344924,0.0001215226,0.0004392019,0.0004370245],"domain_scores_gemma":[0.9991992,0.00004089271,0.0001656709,0.000160683,0.000144379,0.0002891466],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00003248376,0.00005170396,0.07986528,0.00002152837,0.00001024339,0.000004866051,0.704211,0.0002337995,0.000002156496,0.1868785,0.01133204,0.01735635],"study_design_scores_gemma":[0.000248427,0.0001370907,0.03772186,0.00007615679,0.000003374004,7.578001e-7,0.7001712,0.0003641869,0.00000852053,0.0001535192,0.2607598,0.0003549992],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.3644658,0.00001554724,0.0002584157,0.00248359,0.000683912,0.0003856901,0.00001143065,0.00006790541,0.6316277],"genre_scores_gemma":[0.9984385,0.00002818072,0.00002891633,0.001113541,0.00005242376,0.00001683127,0.00001203788,0.000001011167,0.0003085579],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6339727,"threshold_uncertainty_score":0.9242022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1066176342857003,"score_gpt":0.3142840655393569,"score_spread":0.2076664312536566,"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."}}