{"id":"W2169045883","doi":"10.1111/imre.12110","title":"Sorting or Shaping? The Gendered Economic Outcomes of Immigration Policy in Canada","year":2014,"lang":"en","type":"article","venue":"International Migration Review","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":46,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Disadvantage; Immigration; Employability; Immigration policy; Demographic economics; Earnings; Human capital; Context (archaeology); Economics; Unemployment; Labour economics; Political science; Economic growth; Geography","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":[0.001879025,0.0002279007,0.0004831754,0.001483003,0.002734355,0.003006189,0.001068505,0.000652559,0.002758543],"category_scores_gemma":[0.004670792,0.0001244232,0.000366392,0.003922766,0.002627229,0.0007881055,0.00107633,0.0006321808,0.0001800532],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03461251,"about_ca_system_score_gemma":0.05074984,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9880483,"about_ca_topic_score_gemma":0.9907343,"domain_scores_codex":[0.9990807,0.0001418683,0.00002178669,0.00009102493,0.00019034,0.0004743365],"domain_scores_gemma":[0.9983568,0.0002552918,0.0003000884,0.00007687887,0.0006205215,0.0003905231],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003401694,0.0001134985,0.7399122,0.0003340971,0.0002174519,0.0004635255,0.01777024,0.004403742,0.0005166481,0.06625264,0.017652,0.1520239],"study_design_scores_gemma":[0.00001193457,0.00002276201,0.9554048,0.0003186283,0.00005585958,0.00005050455,0.01712627,0.001469222,0.0001384568,0.004495444,0.02085845,0.00004764195],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9440523,0.0160972,0.0002572485,0.01021596,0.00009677604,0.00001975315,0.001281563,0.00001113669,0.02796801],"genre_scores_gemma":[0.9909198,0.005885934,0.0001229996,0.0003053255,0.00001678113,0.000005896577,0.0003036812,0.000006750532,0.002432808],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03461251,"threshold_uncertainty_score":0.2511325,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0334956829809309,"score_gpt":0.3456400281992547,"score_spread":0.3121443452183237,"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."}}