{"id":"W2766753014","doi":"10.1080/13545701.2017.1383618","title":"Gender Inequalities in Labor Market Outcomes of Informal Caregivers near Retirement Age in Urban China","year":2017,"lang":"en","type":"article","venue":"Feminist Economics","topic":"Intergenerational Family Dynamics and Caregiving","field":"Social Sciences","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Central University of Finance and Economics; National Natural Science Foundation of China; International Development Research Centre","keywords":"Grandchild; Earnings; Inequality; Demographic economics; Longitudinal study; Health and Retirement Study; China; Longitudinal data; Ordinary least squares; Gender inequality; Labour economics; Economics; Medicine; Gerontology; Psychology; Demography; Grandparent; Political science; Sociology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.000369326,0.000172963,0.0001773367,0.0008873115,0.0005519505,0.0003571604,0.0001880415,0.0001646561,0.001530107],"category_scores_gemma":[0.0008416272,0.00009363011,0.0002056777,0.0007201778,0.000340774,0.0003006834,0.0005717441,0.0002057295,0.0001067574],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005437155,"about_ca_system_score_gemma":0.0005238336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03688505,"about_ca_topic_score_gemma":0.09039202,"domain_scores_codex":[0.9997779,0.00003393643,0.00001294471,0.00003182486,0.00003556491,0.0001079145],"domain_scores_gemma":[0.9995466,0.0000493433,0.0001808916,0.00002887349,0.00004821962,0.0001460624],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003479567,0.00003081362,0.9946457,0.000007913283,0.000023728,0.0001236878,0.001189941,0.00007470339,0.0001859051,0.0002776457,0.0001349511,0.003270238],"study_design_scores_gemma":[0.000001183261,0.000009807197,0.9988367,0.000004219705,0.000004275863,0.00001711944,0.0008068489,0.0001065875,0.00001790081,0.00007350511,0.0001204011,0.000001545929],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995578,0.00007866258,0.00001541304,0.00004630402,0.000001706578,0.000001214742,0.00006063872,5.425836e-7,0.0002376782],"genre_scores_gemma":[0.9997193,0.00003989759,0.000006394063,0.000008917174,0.000001734208,0.000001155417,0.00005326092,2.477338e-7,0.0001689924],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03688505,"threshold_uncertainty_score":0.07334071,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02610166450681864,"score_gpt":0.2840648497300686,"score_spread":0.25796318522325,"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."}}