{"id":"W4365453475","doi":"10.3390/economies11040114","title":"Effects of Spatial Characteristics on Non-Standard Employment for Canada’s Immigrant Population","year":2023,"lang":"en","type":"article","venue":"Economies","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Census; Microdata (statistics); Demographic economics; American Community Survey; Metropolitan area; Geography; Population; Spatial mismatch; Ordinary least squares; Demography; Economics; Sociology; Econometrics","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":[0.0008082126,0.0003256177,0.0002905977,0.001216519,0.002093805,0.001322345,0.0009323873,0.0003579151,0.003609647],"category_scores_gemma":[0.004626496,0.0001496076,0.0008517157,0.002344177,0.001130686,0.0003642168,0.001804354,0.000583174,0.00025534],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0059939,"about_ca_system_score_gemma":0.01282476,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9171227,"about_ca_topic_score_gemma":0.961651,"domain_scores_codex":[0.9991269,0.0001447465,0.00004983848,0.0001169775,0.0002292288,0.0003323179],"domain_scores_gemma":[0.9962848,0.0005688286,0.001002592,0.0002684152,0.0008626373,0.001012636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00006375698,0.00002123544,0.9945532,0.00001103732,0.00005528568,0.00008431047,0.0004860643,0.0003837872,0.00005770695,0.0002988094,0.0004535377,0.003531273],"study_design_scores_gemma":[0.000002305751,0.00002540098,0.9956676,0.00002375197,0.00001967208,0.00002885454,0.00286658,0.0007096586,0.00003045488,0.0000794834,0.0005395815,0.000006719797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9965644,0.0002589759,0.0001375768,0.0002289121,0.00001382413,0.00001139636,0.001077196,0.000010241,0.001697521],"genre_scores_gemma":[0.9986024,0.0001188088,0.00007690593,0.00001620939,0.000003512848,0.000005461605,0.0005163933,0.000002837391,0.0006573368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08287734,"threshold_uncertainty_score":0.1667308,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007704508961216249,"score_gpt":0.2545777530493037,"score_spread":0.2468732440880874,"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."}}