{"id":"W3010445673","doi":"10.1007/978-981-10-1491-8_5","title":"China’s Fertility Policies and Canada’s Immigration Policies: A Comparative Study of Their Impacts on Population Aging","year":2020,"lang":"en","type":"book-chapter","venue":"Research series on the Chinese dream and China's development path","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Immigration; China; Population ageing; Fertility; Population; Immigration policy; Demographic economics; Total fertility rate; Development economics; Geography; Political science; Economic growth; Demography; Economics; Sociology; Research methodology; Family planning","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":[0.000651861,0.0001907973,0.0002472838,0.001608559,0.003050913,0.001701795,0.0007249425,0.0004440564,0.004355977],"category_scores_gemma":[0.001661922,0.0001153273,0.0003878982,0.005939946,0.001300508,0.0007178615,0.001000015,0.0006540658,0.0001317699],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03713652,"about_ca_system_score_gemma":0.06456531,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9865328,"about_ca_topic_score_gemma":0.9952864,"domain_scores_codex":[0.9995424,0.00006107917,0.00001287748,0.00002875485,0.0001155105,0.000239513],"domain_scores_gemma":[0.9989038,0.0002140012,0.0001521744,0.00003017712,0.0003664533,0.000333523],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002881917,0.0002057966,0.7964233,0.0002594278,0.0001815839,0.0007037474,0.02256247,0.002225242,0.0004368995,0.06599487,0.02997214,0.08074634],"study_design_scores_gemma":[0.00001197081,0.0000438433,0.9539107,0.0001002667,0.00006012498,0.00004935042,0.01893872,0.0005859627,0.000145213,0.0008079802,0.02532134,0.00002454833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.946789,0.008186834,0.00007261297,0.006087339,0.00007835281,0.0000233086,0.002273251,0.00001270539,0.03647657],"genre_scores_gemma":[0.9855909,0.005078232,0.000100179,0.000338055,0.00002271253,0.00001296928,0.0006960858,0.000006054616,0.008154829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9628635,"threshold_uncertainty_score":0.2694456,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03641366389646766,"score_gpt":0.3252283383765723,"score_spread":0.2888146744801046,"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."}}