{"id":"W4233685873","doi":"10.3138/cpp.37.4.495","title":"Quantifying the Effects of the Provincial Nominee Programs","year":2011,"lang":"en","type":"article","venue":"Canadian Public Policy","topic":"Migration and Labor Dynamics","field":"Social Sciences","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg","funders":"","keywords":"Immigration; Demographic economics; Political science; New immigrants; Economic growth; Geography; Socioeconomics; Economics; Law","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":[0.00447648,0.0002726304,0.0004065758,0.001001221,0.001725485,0.001484527,0.001124731,0.0004596324,0.002380867],"category_scores_gemma":[0.02282234,0.0001672845,0.0004282556,0.002091809,0.0009908477,0.0005418923,0.00184706,0.0009192781,0.0001493403],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02129219,"about_ca_system_score_gemma":0.03197668,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9094169,"about_ca_topic_score_gemma":0.9506131,"domain_scores_codex":[0.9941154,0.002186148,0.0001390521,0.0003186184,0.001198185,0.002042621],"domain_scores_gemma":[0.9888654,0.003370471,0.002553323,0.0004820351,0.002904713,0.001823935],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006972684,0.0004537913,0.9264997,0.0001795013,0.0002300817,0.0001063599,0.001449185,0.01000132,0.0008898676,0.005253224,0.002441532,0.05179824],"study_design_scores_gemma":[0.00003888387,0.0004024623,0.9875423,0.00004609812,0.0001267326,0.00001581196,0.002410305,0.004067063,0.0004428402,0.0004198709,0.004475336,0.00001236008],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9844974,0.0003495117,0.0007269435,0.0008940817,0.00002235184,0.000192447,0.00136862,0.00001839298,0.01193029],"genre_scores_gemma":[0.9963787,0.0002095119,0.00067775,0.0001235958,0.00001031294,0.00008105368,0.000464286,0.000004229731,0.002050551],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.09058309,"threshold_uncertainty_score":0.182233,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04310436916240171,"score_gpt":0.2822208296341531,"score_spread":0.2391164604717514,"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."}}