{"id":"W3161034244","doi":"10.1139/facets-2021-0014","title":"Supporting Canada’s COVID-19 resilience and recovery through robust immigration policy and programs","year":2021,"lang":"en","type":"article","venue":"FACETS","topic":"Migration, Health and Trauma","field":"Psychology","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Laurentian University; Mount Royal University; Wilfrid Laurier University; Positive Living Society of British Columbia; University of Toronto; Toronto Metropolitan University; Queen's University; Nipissing University; Western University","funders":"","keywords":"Immigration; Immigration policy; Refugee; Political science; Residence; Pandemic; Government (linguistics); Economic growth; Resilience (materials science); Immigration law; Coronavirus disease 2019 (COVID-19); Development economics; Demographic economics; Economics; Medicine; Law; Infectious disease (medical specialty)","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001913974,0.0001030185,0.0001327913,0.00003076759,0.0002269456,0.00004857154,0.00004490942,0.00008247276,0.0001729893],"category_scores_gemma":[0.0003241292,0.0001040431,0.00001427766,0.0001777313,0.00004475763,0.0001200215,0.00002282528,0.0001082056,0.00000657826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001110326,"about_ca_system_score_gemma":0.001892043,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6261432,"about_ca_topic_score_gemma":0.9263625,"domain_scores_codex":[0.9988087,0.0001055131,0.000255439,0.0003455313,0.000131477,0.0003533773],"domain_scores_gemma":[0.9993178,0.00008948419,0.0001060735,0.0001900778,0.00005234668,0.0002442725],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002758777,0.0003080192,0.476019,0.0008183991,0.000127002,0.0004495749,0.08981189,0.0002327725,0.0006305507,0.03768215,0.2311393,0.1625055],"study_design_scores_gemma":[0.002112687,0.0003562368,0.4126679,0.00006330023,0.00003922492,0.0006721811,0.0240925,0.0002527867,0.000470252,0.003101822,0.5555485,0.0006225838],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9780639,0.001484577,0.001477991,0.01348951,0.0002883913,0.0003270625,0.00003908545,0.00004719533,0.004782305],"genre_scores_gemma":[0.989758,0.0001483824,0.0007194223,0.004955571,0.0001258049,0.00003050111,0.0001006776,0.00001018751,0.00415151],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3244092,"threshold_uncertainty_score":0.4242754,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03908523992865735,"score_gpt":0.364632914051913,"score_spread":0.3255476741232556,"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."}}