{"id":"W4283528853","doi":"10.1111/cag.12785","title":"Geo‐scripts and refugee resettlement in Canada: Designations and destinations","year":2022,"lang":"en","type":"article","venue":"Canadian Geographies / Géographies canadiennes","topic":"Migration, Refugees, and Integration","field":"Social Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Social Sciences and Humanities Research Council of Canada","keywords":"Refugee; Government (linguistics); Settlement (finance); Livelihood; Economic growth; Political science; Immigration; Displaced person; Destinations; Geography; Business; Law; Tourism; Economics; Agriculture","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000683446,0.0002606336,0.0002207094,0.001464593,0.01427695,0.004450373,0.0009789151,0.0003453166,0.004661396],"category_scores_gemma":[0.001936897,0.0001959932,0.000240029,0.003296978,0.006809228,0.001158843,0.004023617,0.0009715664,0.0002290101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.06020024,"about_ca_system_score_gemma":0.08756919,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9962103,"about_ca_topic_score_gemma":0.9986323,"domain_scores_codex":[0.9991741,0.0001372416,0.00003154458,0.00007233143,0.0001694209,0.0004153889],"domain_scores_gemma":[0.9988563,0.00009523465,0.0001375513,0.00003606425,0.0003613388,0.0005134947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001017303,0.00005648821,0.2691531,0.0002292801,0.00002312804,0.001397274,0.5769621,0.00112309,0.0006860246,0.06880217,0.01753168,0.06393401],"study_design_scores_gemma":[0.000005408606,0.00002072275,0.1998829,0.0002919926,0.00001269769,0.0002289587,0.740089,0.0003252623,0.0001836383,0.001251847,0.05764218,0.00006543505],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9298328,0.001538183,0.0005773305,0.004141891,0.00006214563,0.0000669458,0.00108065,0.00003046663,0.06266959],"genre_scores_gemma":[0.9901996,0.001017875,0.0003636893,0.0001545597,0.000002876196,0.00001926162,0.0002904095,0.00001259217,0.00793915],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06020024,"threshold_uncertainty_score":0.4367853,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01314125892296892,"score_gpt":0.2220523536660001,"score_spread":0.2089110947430312,"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."}}