{"id":"W1527340500","doi":"10.7202/800848ar","title":"La mobilité interprovinciale de la main-d’oeuvre au Canada : le cas de l’Ontario, de la Nouvelle-Écosse et du Nouveau-Brunswick","year":2009,"lang":"en","type":"article","venue":"L Actualité économique","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Nova scotia; Unemployment; Ordinary least squares; Geography; Emigration; Welfare economics; Economics; Demographic economics; Econometrics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0002987635,0.0002553526,0.0002064307,0.001298265,0.002628718,0.00144278,0.0005130862,0.0002671675,0.002371165],"category_scores_gemma":[0.001068635,0.0001751691,0.0003621778,0.002191139,0.001114619,0.0005899396,0.0006858769,0.0004039624,0.0001579294],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04057271,"about_ca_system_score_gemma":0.03700772,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9980214,"about_ca_topic_score_gemma":0.9992204,"domain_scores_codex":[0.9996734,0.00002332798,0.000008093928,0.0000390255,0.00008649949,0.0001696754],"domain_scores_gemma":[0.9993469,0.00007872876,0.0001311856,0.00001811316,0.0002587526,0.0001662866],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001987758,0.00004166198,0.9088593,0.0001117017,0.0001382943,0.0006886711,0.01184807,0.005165499,0.001310339,0.01125878,0.003443251,0.05693571],"study_design_scores_gemma":[0.00001074035,0.00002437403,0.9675395,0.00007598737,0.00004466875,0.0001181425,0.007734765,0.002764172,0.0003059804,0.0004223693,0.0209264,0.00003283274],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9885203,0.001380681,0.0003532617,0.001009228,0.00001300019,0.0000124776,0.0008183136,0.0000118431,0.007880914],"genre_scores_gemma":[0.993506,0.0007595887,0.0003282854,0.00003721038,0.000003870734,0.000005210261,0.000327306,0.000005262034,0.005027326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04057271,"threshold_uncertainty_score":0.294377,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007923416405028139,"score_gpt":0.2514568748853098,"score_spread":0.2435334584802817,"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."}}