{"id":"W1491391816","doi":"10.1111/coep.12071","title":"PRIVATIZATION IN CHINA: TECHNOLOGY AND GENDER IN THE MANUFACTURING SECTOR","year":2014,"lang":"en","type":"article","venue":"Contemporary Economic Policy","topic":"Labor market dynamics and wage inequality","field":"Economics, Econometrics and Finance","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Carleton University","funders":"","keywords":"Productivity; Wage; Production (economics); Labour economics; Panel data; China; Economics; Business; Demographic economics; Econometrics; Economic growth; Microeconomics","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":[0.0006222735,0.0001429333,0.0002002543,0.0008166732,0.0008283617,0.0007206055,0.000253237,0.0002843623,0.002794734],"category_scores_gemma":[0.001196479,0.0001097451,0.0002856691,0.001417434,0.0008371762,0.0007880184,0.0008591478,0.0003389127,0.000128258],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002333008,"about_ca_system_score_gemma":0.001886928,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04794744,"about_ca_topic_score_gemma":0.07485465,"domain_scores_codex":[0.9995154,0.00006412007,0.00002322838,0.00006147449,0.0001084259,0.0002273575],"domain_scores_gemma":[0.9988519,0.0001427395,0.0006818938,0.00005394416,0.00008328664,0.0001863003],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001172376,0.00008550844,0.9773794,0.00003304402,0.00003316776,0.000364097,0.0014839,0.001048522,0.0009734898,0.004064731,0.0004635227,0.01395342],"study_design_scores_gemma":[0.000003290362,0.00004034515,0.9970602,0.0000107539,0.000006823917,0.00003145993,0.0007549286,0.0006718134,0.0001852542,0.0005117445,0.0007196329,0.000003641002],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9980654,0.0002421057,0.00007981849,0.0003199421,0.00000410567,0.000004269694,0.00006966914,0.000002345502,0.001212253],"genre_scores_gemma":[0.999428,0.00008577156,0.00001244102,0.0000257613,0.000004404399,0.000001279472,0.00004175184,4.104425e-7,0.0004001876],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04794744,"threshold_uncertainty_score":0.09533668,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03170612572112049,"score_gpt":0.2379751744551916,"score_spread":0.2062690487340711,"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."}}