{"id":"W4379933303","doi":"10.1016/j.ssmqr.2023.100293","title":"Divided in a digital economy: Understanding disability employment inequities stemming from the application of advanced workplace technologies","year":2023,"lang":"en","type":"article","venue":"SSM - Qualitative Research in Health","topic":"Retirement, Disability, and Employment","field":"Social Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Institute for Work & Health; McMaster University; University of British Columbia; Public Health Ontario; BC Children's Hospital; University of Toronto","funders":"Canadian Arthritis Network; Social Sciences and Humanities Research Council of Canada; Arthritis Society","keywords":"Digital economy; Digital transformation; Work (physics); Equity (law); Public relations; Business; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"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":[0.006760984,0.0003202119,0.0004735886,0.003691345,0.009932573,0.008216067,0.001604217,0.00152207,0.002929994],"category_scores_gemma":[0.01053509,0.000295756,0.0004056623,0.002966602,0.01288746,0.01035781,0.01386744,0.002721526,0.0001176342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01181655,"about_ca_system_score_gemma":0.01107215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0846314,"about_ca_topic_score_gemma":0.1031546,"domain_scores_codex":[0.994964,0.00215759,0.0002116533,0.000346359,0.0008071171,0.001513281],"domain_scores_gemma":[0.9951668,0.00262584,0.0007519176,0.0001607603,0.0005685067,0.0007262545],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.00002735917,0.00009505104,0.0401503,0.0001697342,0.00001456396,0.0005115058,0.9003786,0.0001413207,0.0002271243,0.03464651,0.0004380044,0.02319991],"study_design_scores_gemma":[0.000002436664,0.00001743761,0.01170524,0.000274421,0.000008393119,0.0001546699,0.9759566,0.0002198827,0.00006141618,0.007116887,0.004473772,0.000008906083],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9710829,0.00152993,0.00151217,0.007499703,0.00003526281,0.00004094472,0.0000443702,0.000004098885,0.01825059],"genre_scores_gemma":[0.9987186,0.0004232895,0.000199071,0.0002784845,0.000007646911,0.00001909464,0.00001111253,0.000002301026,0.0003405313],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0846314,"threshold_uncertainty_score":0.1682776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6842742289283648,"score_gpt":0.6199957660232356,"score_spread":0.06427846290512917,"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."}}