{"id":"W1552287269","doi":"","title":"Women in Higher Education in Argentina: Equality or Job Feminization","year":2009,"lang":"en","type":"article","venue":"Canadian women's studies","topic":"Gender and Feminist Studies","field":"Social Sciences","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Feminization (sociology); Gender equality; Gender studies; Demographic economics; Political science; Sociology; Economics","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":[0.001174482,0.0002133141,0.0004809909,0.001362314,0.009122594,0.002633389,0.0005924933,0.001268479,0.007993929],"category_scores_gemma":[0.002125183,0.0001562971,0.0001544715,0.002700925,0.004143164,0.001440785,0.001938868,0.001674894,0.0002533438],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01483876,"about_ca_system_score_gemma":0.01294667,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.7257841,"about_ca_topic_score_gemma":0.8661833,"domain_scores_codex":[0.9984871,0.0003069435,0.00002045817,0.00008120925,0.0001187099,0.0009855597],"domain_scores_gemma":[0.9990013,0.0002426405,0.0001362637,0.0000259444,0.0001666618,0.0004272059],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"observational","study_design_scores_codex":[0.0005276442,0.0005502842,0.2473977,0.0004647119,0.00003436343,0.002315518,0.3711983,0.0004130533,0.00192437,0.2502401,0.02316948,0.1017645],"study_design_scores_gemma":[0.00003072571,0.00007345851,0.484121,0.0004081689,0.0000194234,0.000296577,0.3670237,0.0001700477,0.0003239028,0.003571017,0.143935,0.00002688753],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8457334,0.006198118,0.0001446386,0.01831529,0.000181314,0.00002892771,0.0002644594,0.000008361357,0.1291255],"genre_scores_gemma":[0.9863489,0.001474721,0.00006106439,0.0005819632,0.00004959483,0.000008845978,0.00006020453,0.000005115418,0.01140971],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7257841,"threshold_uncertainty_score":0.5516616,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08815040465014463,"score_gpt":0.3512175501047062,"score_spread":0.2630671454545616,"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."}}