{"id":"W1923471031","doi":"10.3968/j.css.1923669720090503.005","title":"Chinese Social Pension Insurance System: Improvement and Development","year":2009,"lang":"en","type":"article","venue":"Canadian social science","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social pension; Social insurance; Pension system; Pension; Political science; Pension insurance; Welfare economics; Humanities; Economics; Law; Art","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001404818,0.000213418,0.0001669271,0.00162387,0.002189992,0.001135158,0.0005085548,0.0003880256,0.003999892],"category_scores_gemma":[0.001685984,0.0001005792,0.0002228367,0.001841583,0.0008583569,0.001209432,0.001412096,0.0004245706,0.0001468908],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01057153,"about_ca_system_score_gemma":0.01754661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.2168936,"about_ca_topic_score_gemma":0.2271562,"domain_scores_codex":[0.9994262,0.00008584728,0.00004637969,0.00003341139,0.0001481893,0.0002600215],"domain_scores_gemma":[0.9995263,0.00005213141,0.00008243523,0.00003764939,0.0001447484,0.0001567509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002774799,0.0002470814,0.4911648,0.0008734362,0.00009212818,0.001216137,0.05474481,0.002186391,0.004214184,0.1047077,0.02026808,0.3200077],"study_design_scores_gemma":[0.00003163331,0.0002036667,0.8280679,0.0001768424,0.00005593553,0.0003491086,0.02027868,0.002287432,0.001440973,0.003529351,0.1435297,0.00004874797],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9605357,0.004321034,0.0005105257,0.009938462,0.00009304947,0.00009421009,0.000392446,0.0000411871,0.02407333],"genre_scores_gemma":[0.991847,0.002082243,0.0004343832,0.0002650151,0.00002887356,0.0000261477,0.0002158115,0.00000445902,0.005095978],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2168936,"threshold_uncertainty_score":0.4312622,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008697342378022213,"score_gpt":0.2631659413956441,"score_spread":0.2544685990176219,"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."}}