{"id":"W2900674953","doi":"10.1007/s12122-020-09316-1","title":"Linguistic Distance, Languages of Work and Wages of Immigrants in Montreal","year":2021,"lang":"en","type":"preprint","venue":"Journal of Labor Research","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"University of Ottawa","keywords":"Immigration; Earnings; Microdata (statistics); Linguistics; Metropolitan area; French; Context (archaeology); Demographic economics; First language; Census; Political science; Geography; Sociology; Economics; Population; Demography; Law; Accounting","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005114141,0.0003691956,0.0003644955,0.001667279,0.003030367,0.001687461,0.0009409474,0.0004823387,0.007039233],"category_scores_gemma":[0.00269457,0.0002175467,0.0003381164,0.002892689,0.001270657,0.0006479334,0.001238065,0.0006492606,0.0003780751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01346809,"about_ca_system_score_gemma":0.009249402,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9857852,"about_ca_topic_score_gemma":0.9924783,"domain_scores_codex":[0.9995041,0.0001036961,0.00002339392,0.00008975093,0.00007851498,0.0002006234],"domain_scores_gemma":[0.998897,0.0001494502,0.0002545297,0.00003328076,0.0002888017,0.0003769074],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003363635,0.0001246717,0.9677825,0.00004194058,0.0001021732,0.0003320457,0.01837271,0.0003327061,0.001087148,0.001157851,0.001715412,0.008614593],"study_design_scores_gemma":[0.000009121974,0.00002694516,0.9875552,0.00001539282,0.00001434201,0.00003071291,0.0108246,0.0001593162,0.00006430269,0.00006377436,0.001219012,0.00001708831],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9975352,0.0001550171,0.00002825597,0.0002307106,0.000006525877,0.00001005397,0.0005501764,0.000004068442,0.001480053],"genre_scores_gemma":[0.9966934,0.0001073591,0.00004590518,0.00004194921,0.000004433934,0.0000115042,0.0002540596,0.000004970741,0.002836416],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01421481,"threshold_uncertainty_score":0.0977183,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05376247067833957,"score_gpt":0.417825526240493,"score_spread":0.3640630555621535,"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."}}