{"id":"W1501325849","doi":"","title":"Financial Security of Elders in China","year":2009,"lang":"en","type":"preprint","venue":"RePEc: Research Papers in Economics","topic":"Migration, Aging, and Tourism Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"China; Geographer; Social security; Government (linguistics); Old Age Security; Pension; Pillar; Financial security; Population; Economic growth; Perspective (graphical); Finance; Development economics; Business; Geography; Economics; Economic geography; Market economy; Sociology","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":[0.0008553605,0.0001620219,0.0002436757,0.001325132,0.0009521287,0.0008550948,0.0002280907,0.0003071996,0.001719128],"category_scores_gemma":[0.001696377,0.00007162766,0.0001671794,0.001466192,0.0005235558,0.0007853474,0.000994475,0.0003203074,0.0001222586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001643004,"about_ca_system_score_gemma":0.002645399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04823944,"about_ca_topic_score_gemma":0.04931944,"domain_scores_codex":[0.9997322,0.00003988577,0.00001964649,0.00002630834,0.00006115868,0.0001207384],"domain_scores_gemma":[0.9991929,0.00005705588,0.0003302666,0.0000330666,0.0001338353,0.0002528233],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000818937,0.00007327489,0.9416502,0.00007956439,0.0000501417,0.0006071044,0.003596407,0.0009910167,0.0003414288,0.01309052,0.006344389,0.03309407],"study_design_scores_gemma":[0.00001127419,0.00007287941,0.9840623,0.00007759764,0.00002275825,0.000180626,0.002930066,0.001923542,0.0001206148,0.003750443,0.006829018,0.00001893878],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9920121,0.0008996055,0.00009207514,0.002288918,0.00002296237,0.000009382004,0.0004194592,0.000003528043,0.004251882],"genre_scores_gemma":[0.9981676,0.000698357,0.00004087242,0.0001691866,0.00001976521,0.000004493418,0.0001976164,4.870301e-7,0.0007015156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04823944,"threshold_uncertainty_score":0.09591728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02150815592644167,"score_gpt":0.3344814697138775,"score_spread":0.3129733137874359,"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."}}