{"id":"W7098569737","doi":"","title":"MSc International Economics Is the Grass Really Fairer on the Other Side? Migration and Inequality in Canada","year":2015,"lang":"en","type":"article","venue":"","topic":"Plant Ecology and Taxonomy Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Inequality; Unemployment; Per capita; Economic inequality; Net migration rate; Gini coefficient; International comparisons","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":[0.0006307861,0.0001620175,0.0003685787,0.001278149,0.003965591,0.003130193,0.0005648168,0.000422577,0.008187581],"category_scores_gemma":[0.004101855,0.00007243426,0.0002135898,0.004045033,0.002830217,0.001028027,0.0009719571,0.0009397147,0.0002666848],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04077664,"about_ca_system_score_gemma":0.05710857,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9956198,"about_ca_topic_score_gemma":0.9971867,"domain_scores_codex":[0.9991748,0.00006626587,0.0000133866,0.00007154371,0.0002124599,0.000461529],"domain_scores_gemma":[0.998516,0.0001918695,0.0001998294,0.00004789214,0.0005438176,0.0005005485],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002949014,0.00007558051,0.5498909,0.0002631202,0.0001748955,0.0005708732,0.01062231,0.004344207,0.0005682869,0.2086156,0.06187505,0.1627043],"study_design_scores_gemma":[0.00002279756,0.00002996256,0.8407307,0.0004358742,0.00009483395,0.0001191008,0.0276218,0.002878399,0.000283891,0.01525262,0.1124671,0.0000629905],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7392049,0.01177949,0.001324578,0.06716635,0.00027683,0.00003931147,0.002763021,0.00004515149,0.1774002],"genre_scores_gemma":[0.9872316,0.002804871,0.0003279277,0.0008336357,0.00003580647,0.000004616629,0.0002469556,0.00001309311,0.008501559],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04077664,"threshold_uncertainty_score":0.2958566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05378517864274707,"score_gpt":0.2031468670398407,"score_spread":0.1493616883970937,"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."}}