{"id":"W3124502678","doi":"","title":"Immmigration and Internal Mobility in Canada","year":2014,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inflow; Immigration; Matching (statistics); Demographic economics; Economics; Point (geometry); Point system; Net migration rate; Internal migration; Geography; Labour economics; Population; Economic growth; Demography; Mathematics; Sociology; Developing country; Statistics","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":[0.0003427174,0.0005229666,0.0005672595,0.001984496,0.00414303,0.002484804,0.001013758,0.0004666396,0.006066828],"category_scores_gemma":[0.001795432,0.000173311,0.0006422579,0.00388692,0.001531161,0.0004688649,0.002161372,0.0008170451,0.0003484165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04984971,"about_ca_system_score_gemma":0.03753331,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9954649,"about_ca_topic_score_gemma":0.9963464,"domain_scores_codex":[0.9994782,0.00002645309,0.000007664004,0.00004493818,0.0001055364,0.0003372826],"domain_scores_gemma":[0.9990932,0.00009555695,0.000190118,0.00003258014,0.0002528717,0.0003358079],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003474097,0.0002675658,0.777763,0.0001994653,0.0002412189,0.0008935124,0.005016555,0.06311382,0.001095558,0.07060236,0.01346588,0.06699364],"study_design_scores_gemma":[0.000062182,0.000128416,0.8852186,0.0001839188,0.0002061776,0.0002072172,0.01421454,0.06918366,0.0009862662,0.0071397,0.02234467,0.0001246779],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9817707,0.001030466,0.0005596511,0.0009470384,0.0000199555,0.00001877106,0.001246991,0.00004724047,0.01435908],"genre_scores_gemma":[0.9942597,0.0007380156,0.0002577256,0.00005040258,0.00000472833,0.000005772116,0.000524251,0.000009956557,0.004149371],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04984971,"threshold_uncertainty_score":0.3616866,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0195535674063667,"score_gpt":0.3207510496925542,"score_spread":0.3011974822861875,"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."}}