{"id":"W4393901926","doi":"10.1017/s096318012400015x","title":"Ethical and Equitable Digital Health Research: Ensuring Self-Determination in Data Governance for Racialized Communities","year":2024,"lang":"en","type":"article","venue":"Cambridge Quarterly of Healthcare Ethics","topic":"Focus Groups and Qualitative Methods","field":"Social Sciences","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Royal University; University of Calgary","funders":"","keywords":"Health equity; Indigenous; Data governance; Public relations; Equity (law); Digital health; Corporate governance; Stewardship (theology); Sociology; Scholarship; Political science; Health care; Business; Law; Data quality; Politics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","research_integrity"],"consensus_categories":[],"category_scores_codex":[0.04742151,0.0001347515,0.0003943325,0.0001781938,0.001008165,0.0003204623,0.0004971545,0.0004529596,0.000002356097],"category_scores_gemma":[0.002973856,0.0001404584,0.00004715744,0.0005026815,0.0009308505,0.0006924156,0.0001261426,0.002512674,0.000001938555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003348811,"about_ca_system_score_gemma":0.002118376,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02435517,"about_ca_topic_score_gemma":0.02803228,"domain_scores_codex":[0.9908219,0.006391504,0.000664401,0.000398496,0.0009574805,0.0007662122],"domain_scores_gemma":[0.9825062,0.01619225,0.000145192,0.0004337025,0.000535633,0.0001870273],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00004074148,0.00003456269,0.00008285639,0.002706467,0.000008657777,0.000003426301,0.2852812,1.266352e-7,0.000005155671,0.5241643,0.001199666,0.1864729],"study_design_scores_gemma":[0.001373818,0.00373018,0.001800335,0.00482416,0.00001698011,0.00001178129,0.4856223,0.008783076,0.00002596828,0.06397664,0.4291647,0.0006700807],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.1928951,0.03820138,0.02894264,0.726348,0.002343932,0.003957218,0.003847523,0.0004713258,0.002992866],"genre_scores_gemma":[0.9888326,0.001668385,0.008323296,0.0004887205,0.0002259554,0.00005564219,0.0001072539,0.00002816785,0.0002699711],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7959375,"threshold_uncertainty_score":0.9997886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5298484946468839,"score_gpt":0.5837452778986664,"score_spread":0.05389678325178249,"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."}}