{"id":"W3092430977","doi":"","title":"저출산 고령화시대 미국, 캐나다, 호주의 이민정책 비교 연구: 이민인구와 최근 경향을 중심으로","year":2020,"lang":"ko","type":"article","venue":"한국비교정부학보","topic":"Korean Urban and Social Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Immigration; Immigration policy; Population; Demographic economics; Political science; Geography; Economic growth; Development economics; Demography; Economics; Sociology","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":[0.001414645,0.000171574,0.000181956,0.001509332,0.001529583,0.002202279,0.0003222706,0.0001542077,0.003992646],"category_scores_gemma":[0.003412395,0.00009720138,0.0002570378,0.003304007,0.0006075348,0.0006858338,0.0005202992,0.0003162424,0.0006947384],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007098177,"about_ca_system_score_gemma":0.01875456,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5527168,"about_ca_topic_score_gemma":0.6315028,"domain_scores_codex":[0.9989941,0.0001658194,0.0001166508,0.0001515231,0.0003267245,0.0002451741],"domain_scores_gemma":[0.9984508,0.0001787869,0.000354205,0.00004504732,0.0008096035,0.0001615482],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001210429,0.00009544814,0.8598256,0.0004106522,0.00007392794,0.0001964953,0.00579725,0.0006485891,0.000456421,0.007665025,0.007725613,0.116984],"study_design_scores_gemma":[0.00001401097,0.00009204788,0.953858,0.0002870132,0.0001008315,0.0002305354,0.02246423,0.0009359926,0.0007617618,0.0008352589,0.02038905,0.00003132479],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9570912,0.001983501,0.001856315,0.00204906,0.0001146745,0.0003599428,0.003975706,0.00005022937,0.03251934],"genre_scores_gemma":[0.9832857,0.001657988,0.003940152,0.0005370096,0.00002918486,0.0003011067,0.001931413,0.00001310154,0.008304297],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4472832,"threshold_uncertainty_score":0.8998347,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02366460178079584,"score_gpt":0.2139006377716335,"score_spread":0.1902360359908376,"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."}}