{"id":"W4405486533","doi":"10.1287/orsc.2022.16949","title":"Location Matters: Everyday Gender Discrimination in Remote and On-site Work","year":2024,"lang":"en","type":"article","venue":"Organization Science","topic":"Digital Economy and Work Transformation","field":"Social Sciences","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Work (physics); Sociology; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007143944,0.00005158904,0.00004248681,0.0002426091,0.000274248,0.0006413982,0.000104346,0.00003289197,0.00005413647],"category_scores_gemma":[0.0001534065,0.00005104596,0.000005571328,0.003306876,0.0002325711,0.002291227,0.00001411732,0.00004903476,0.0001851699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001682777,"about_ca_system_score_gemma":0.0001701693,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000059355,"about_ca_topic_score_gemma":0.00007254595,"domain_scores_codex":[0.9992403,0.0000270676,0.000127236,0.0002072545,0.0002548704,0.0001433053],"domain_scores_gemma":[0.9997123,0.0000424496,0.00002228606,0.00006692462,0.0001044878,0.00005150548],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.000009748519,0.00005974039,0.02875595,0.0001204886,0.000004656065,0.000004300186,0.1580715,0.0009456831,0.0004613039,0.4983925,0.001414345,0.3117598],"study_design_scores_gemma":[0.0007250049,0.00009547277,0.8398558,0.001599985,0.0000335863,0.000009390247,0.01689438,0.01345004,0.004846381,0.0388112,0.08240353,0.001275199],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7800198,0.0001977752,0.1075015,0.02722801,0.001341719,0.0006287306,0.000004400336,0.0003695204,0.08270857],"genre_scores_gemma":[0.9988883,0.000054952,0.0001907148,0.0004530663,0.00003929505,0.000001014504,0.000007930913,0.000005441072,0.0003593472],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8110999,"threshold_uncertainty_score":0.6185018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01742541707440528,"score_gpt":0.2713242280405875,"score_spread":0.2538988109661822,"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."}}