{"id":"W1499658182","doi":"","title":"Aging wellbeing and social security in rural northern China.","year":2000,"lang":"en","type":"article","venue":"Population and Development Review","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Social security; China; Rural area; Economic growth; Position (finance); Elderly people; Institution; Economic security; Consumption (sociology); Socioeconomics; Development economics; Demographic economics; Political science; Sociology; Economics; Gerontology; Medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.0003418537,0.0001234482,0.0001751382,0.00071043,0.0004756402,0.0005200191,0.0001078677,0.000137165,0.001353824],"category_scores_gemma":[0.0002701874,0.00005244627,0.00008212652,0.0009198802,0.0003063911,0.0002837932,0.0003703541,0.00009233533,0.00008639372],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000776754,"about_ca_system_score_gemma":0.001545652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02647002,"about_ca_topic_score_gemma":0.06374061,"domain_scores_codex":[0.9999152,0.00003204319,0.000007393876,0.000008512751,0.00002130742,0.00001544804],"domain_scores_gemma":[0.9999111,0.00001522066,0.00003672087,0.000002928954,0.00001613222,0.00001796908],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001068607,0.0001064149,0.3217993,0.005377763,0.0001250678,0.003335108,0.02718966,0.000729918,0.005240486,0.01358703,0.00570133,0.616701],"study_design_scores_gemma":[0.000006865805,0.0002870951,0.8710125,0.001128497,0.0000672667,0.002213056,0.01371438,0.0002353389,0.0004540028,0.001891245,0.1089712,0.00001873066],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6008431,0.364787,0.0003701978,0.003249566,0.0001509891,0.00003486757,0.0001214774,0.00001109427,0.03043162],"genre_scores_gemma":[0.8608487,0.1347877,0.0002233538,0.0002688096,0.00008472429,0.00002114926,0.0000757783,0.000001110089,0.003688657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02647002,"threshold_uncertainty_score":0.05263186,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01059539365876018,"score_gpt":0.2852192141087626,"score_spread":0.2746238204500024,"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."}}