{"id":"W3210057673","doi":"10.18438/eblip29674","title":"Making Job Postings More Equitable: Evidence Based Recommendations from an Analysis of Data Professionals Job Postings Between 2013-2018","year":2020,"lang":"en","type":"article","venue":"Evidence Based Library and Information Practice","topic":"Data Quality and Management","field":"Decision Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University of Illinois at Urbana-Champaign; Florida Institute of Technology; Oregon State University; Georgia State University; University of Massachusetts Amherst; East Carolina University; Drexel University; DePaul University; Johns Hopkins University; Princeton University; University of Washington; Virginia Polytechnic Institute and State University; University of Minnesota; San José State University; University of Texas at Arlington; Harvard University; Georgia Southern University; George Washington University; Western Michigan University; Dartmouth College; York University; University of Miami; Northwestern University; Florida State University; Indiana University Bloomington; San Diego State University; Rice University; Ohio State University; Washington University in St. Louis; City University of New York; North Carolina State University; Reed College; Purdue University; Yale University","keywords":"Professional development; Job analysis; Coding (social sciences); Psychology; Equity (law); Public relations; Medical education; Computer science; Sociology; Medicine; Political science; Job satisfaction; Social psychology","routes":{"ca_aff":false,"ca_fund":true,"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":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.315625,0.001153338,0.002661021,0.01901538,0.007643938,0.01522253,0.009257314,0.003811163,0.00590044],"category_scores_gemma":[0.5825273,0.002233299,0.003535826,0.01753906,0.005465264,0.01962384,0.01700786,0.005854338,0.001483973],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.02000223,"about_ca_system_score_gemma":0.08660506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03044195,"about_ca_topic_score_gemma":0.06767905,"domain_scores_codex":[0.7952052,0.1273025,0.03894233,0.007872959,0.0243983,0.006278824],"domain_scores_gemma":[0.4408498,0.3641534,0.06214989,0.01649351,0.1050126,0.01134085],"domain_codex":null,"domain_gemma":"incentives","domain_candidate":"incentives","domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0009086083,0.001508258,0.2298377,0.07139805,0.001277055,0.0005346905,0.1504914,0.0005762349,0.0003570706,0.003909044,0.03095615,0.5082457],"study_design_scores_gemma":[0.000732776,0.001351092,0.2312652,0.2317118,0.002204753,0.0001815662,0.465813,0.001932757,0.0007918188,0.004292886,0.05938964,0.0003326978],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6535383,0.08144891,0.02929401,0.1512829,0.00461498,0.04164999,0.01202714,0.0004589093,0.02568478],"genre_scores_gemma":[0.8125526,0.03709782,0.1066166,0.01126966,0.0003610127,0.02561131,0.004923509,0.0002070067,0.001360431],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.684375,"threshold_uncertainty_score":0.8439562,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3504512197356653,"score_gpt":0.477853003650539,"score_spread":0.1274017839148736,"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."}}