{"id":"W4386952235","doi":"10.1109/mts.2023.3306526","title":"Diversity Initiatives for Women in IT: Friends or Enemies?","year":2023,"lang":"en","type":"article","venue":"IEEE Technology and Society Magazine","topic":"Gender and Technology in Education","field":"Social Sciences","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Technische Universität München; Bundesministerium für Bildung und Forschung; Australian Government","keywords":"Diversity (politics); Type (biology); Political science; Computer science; Library science; Law; Ecology; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.007425265,0.0004062781,0.0005972543,0.001574324,0.02039638,0.01553942,0.001261415,0.003464247,0.02011144],"category_scores_gemma":[0.01194672,0.0003616199,0.0004766787,0.00213168,0.01254702,0.01435419,0.01838179,0.005949157,0.002117562],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004017049,"about_ca_system_score_gemma":0.005966567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006929215,"about_ca_topic_score_gemma":0.01638037,"domain_scores_codex":[0.9891695,0.006853253,0.0001868011,0.0006145188,0.001394684,0.001781145],"domain_scores_gemma":[0.9852474,0.004208284,0.001083767,0.000655799,0.0007964395,0.008008373],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00008618565,0.0001480892,0.02136902,0.0004782093,0.00004693914,0.0007651367,0.4133057,0.0000490196,0.0006574231,0.1287165,0.1800052,0.2543725],"study_design_scores_gemma":[0.00001807919,0.00009450251,0.00729393,0.0008901168,0.00001750267,0.0004833029,0.3937872,0.00003734869,0.0002396336,0.0258304,0.571273,0.00003500453],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.08914332,0.02630121,0.002220241,0.6761567,0.004320276,0.00004615131,0.0001099203,0.000104223,0.201598],"genre_scores_gemma":[0.8372682,0.01931697,0.001982227,0.07327101,0.003522394,0.0001019307,0.0001133194,0.0001567613,0.0642672],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9796036,"threshold_uncertainty_score":0.06727946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03854909937412968,"score_gpt":0.3367914033562545,"score_spread":0.2982423039821248,"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."}}