{"id":"W2599313167","doi":"","title":"Immigrants sur le marché du travail canadien: qualité, gains et ségrégation","year":2015,"lang":"fr","type":"article","venue":"RePEc: Research Papers in Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Political science; Humanities; Ethnology; Sociology; Philosophy; Law","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002282376,0.0002925176,0.0004049275,0.002175809,0.002378305,0.003974057,0.0006493531,0.0005837345,0.008794017],"category_scores_gemma":[0.0101308,0.0001401569,0.0003591387,0.002929104,0.001728164,0.001347951,0.002834287,0.0008745627,0.0006879213],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002479165,"about_ca_system_score_gemma":0.00192854,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1150689,"about_ca_topic_score_gemma":0.156132,"domain_scores_codex":[0.9987883,0.0003712003,0.0000442284,0.000117222,0.0004049168,0.0002742128],"domain_scores_gemma":[0.9958504,0.001098425,0.001368417,0.0002567003,0.0008537807,0.0005722634],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002679034,0.0001650058,0.871995,0.00007883596,0.0001081851,0.0004700389,0.05819326,0.0004316348,0.0004791949,0.008396821,0.000765982,0.05864811],"study_design_scores_gemma":[0.000005461881,0.0001520843,0.9294701,0.0001217369,0.00006819773,0.0002489163,0.06020138,0.0002633956,0.0003770965,0.002009405,0.007053248,0.00002893325],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.987678,0.0008862488,0.0001504336,0.0004358146,0.0000139168,0.000008784081,0.0001102552,0.000004200591,0.01071232],"genre_scores_gemma":[0.9940932,0.0005622502,0.0001168739,0.0000255054,0.000009399832,0.000007272534,0.0000774518,0.000003400846,0.005104568],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8849311,"threshold_uncertainty_score":0.2287983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07068687253868108,"score_gpt":0.3460127552277674,"score_spread":0.2753258826890863,"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."}}