{"id":"W7100848890","doi":"","title":"NBER WORKING PAPER SERIES TECHNOLOGICAL CHANGE, OCCUPATIONAL TASKS AND DECLINING IMMIGRANT OUTCOMES: IMPLICATIONS FOR EARNINGS AND INCOME INEQUALITY IN CANADA","year":2015,"lang":"en","type":"article","venue":"","topic":"Gender, Labor, and Family Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Earnings; Immigration; Inequality; Economic inequality; Series (stratigraphy); Developed country","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":[0.001775921,0.0003869003,0.001000309,0.002486866,0.00411506,0.003942057,0.001452729,0.0008772083,0.01437597],"category_scores_gemma":[0.005410871,0.0002755372,0.000885359,0.007086041,0.0009415761,0.0009595449,0.001413441,0.001799956,0.00088399],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02992674,"about_ca_system_score_gemma":0.08566467,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9980962,"about_ca_topic_score_gemma":0.9985021,"domain_scores_codex":[0.9988282,0.00007086582,0.00007063163,0.0001213692,0.0003306612,0.0005782711],"domain_scores_gemma":[0.9932161,0.0005668472,0.000907482,0.0001566042,0.0033867,0.001766129],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000318985,0.0001390532,0.8109561,0.0002644332,0.0002923583,0.0003144567,0.001534592,0.001618942,0.000151551,0.01037532,0.1475341,0.02650032],"study_design_scores_gemma":[0.0001014128,0.0000268854,0.9599173,0.0002646315,0.0002020376,0.00004388543,0.004731459,0.001649649,0.0001658629,0.001208639,0.03164126,0.00004699771],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6462259,0.01780067,0.0008805881,0.05066036,0.0006493788,0.0002312796,0.2345217,0.0001812235,0.04884895],"genre_scores_gemma":[0.8816245,0.01017459,0.0007012027,0.001796039,0.0001839579,0.00009295633,0.04973758,0.00007502591,0.05561433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02992674,"threshold_uncertainty_score":0.2171347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1129767423960403,"score_gpt":0.3447215780014278,"score_spread":0.2317448356053875,"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."}}