{"id":"W7132994766","doi":"","title":"Learning how to "Skill" the Self: Citizenship and Immigrant Integration in Toronto, Canada","year":2014,"lang":"","type":"dissertation","venue":"TSpace","topic":"Migration, Ethnicity, and Economy","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Underemployment; Immigration; Government (linguistics); Citizenship; Immigration policy; Coalition government","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":[0.001315767,0.0003383621,0.0004221733,0.0009455155,0.0291117,0.006048706,0.001335719,0.00107759,0.0049361],"category_scores_gemma":[0.001959777,0.0002807164,0.0003002846,0.002428795,0.009586385,0.001611144,0.0043077,0.002646728,0.0002551669],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.1703763,"about_ca_system_score_gemma":0.1942471,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9982236,"about_ca_topic_score_gemma":0.9995118,"domain_scores_codex":[0.9983703,0.0003123421,0.00004119267,0.0001351648,0.0003554217,0.0007855733],"domain_scores_gemma":[0.9976277,0.0002553256,0.0001714264,0.0000495113,0.0005450616,0.001351142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001001234,0.000123962,0.07549534,0.0001812143,0.00002291413,0.001027375,0.826925,0.0003398087,0.0006956101,0.03807282,0.0250736,0.03194219],"study_design_scores_gemma":[0.00001005792,0.00003997767,0.1025088,0.0002614854,0.00002229183,0.0001085853,0.8325661,0.000307824,0.0002290582,0.001022021,0.06287249,0.00005134717],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.930833,0.003524314,0.0001879982,0.0191833,0.0001336299,0.00004850129,0.0002469833,0.00001727069,0.04582509],"genre_scores_gemma":[0.9811633,0.00227992,0.0001661844,0.0009146575,0.00001123109,0.00001603634,0.0001125777,0.0000140886,0.01532207],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1703763,"threshold_uncertainty_score":0.9622459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01223137096250197,"score_gpt":0.2973698474243949,"score_spread":0.2851384764618929,"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."}}