{"id":"W7115170368","doi":"10.1177/17470161251406930","title":"Whose Data, Whose Ethics? Rethinking Ethical Accountability in Research Using Publicly Available Indigenous Data","year":2025,"lang":"en","type":"article","venue":"Research Ethics","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Queen's University","funders":"","keywords":"Indigenous; Sovereignty; Accountability; Research ethics; Interpretation (philosophy); Obligation; Human rights; Operationalization","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":["metaresearch","metaepi_narrow","sts","scholarly_communication","open_science","research_integrity"],"consensus_categories":["metaresearch","sts","research_integrity"],"category_scores_codex":[0.431676,0.0002854839,0.000536154,0.001827939,0.03467998,0.001839971,0.00867062,0.004959665,0.00042199],"category_scores_gemma":[0.03299062,0.0002728229,0.00005360007,0.007306887,0.005909428,0.002231078,0.0008204321,0.04808551,0.0003537642],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003658138,"about_ca_system_score_gemma":0.3445832,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8808125,"about_ca_topic_score_gemma":0.9836894,"domain_scores_codex":[0.9221212,0.05566894,0.00161594,0.003372547,0.01188146,0.005339887],"domain_scores_gemma":[0.9042531,0.07034009,0.0003018512,0.01118388,0.01272539,0.001195635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00009278599,0.000494041,0.004481892,0.0007008415,0.00002944823,0.00002450628,0.7978083,0.000005288435,0.00001574632,0.1925972,0.003253061,0.000496853],"study_design_scores_gemma":[0.0003421951,0.00006321662,0.000605901,0.0007586738,0.00001130487,0.000002314036,0.07055399,0.0008821227,0.00005330045,0.08171886,0.8446726,0.0003355653],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6117623,0.005787108,0.0003680343,0.1674062,0.003097731,0.007281831,0.0005113319,0.0003740219,0.2034114],"genre_scores_gemma":[0.8474318,0.1004303,0.008515014,0.003051898,0.004092625,0.00006806519,0.001656024,0.0001926276,0.03456167],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8414195,"threshold_uncertainty_score":0.9999724,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.761292527785612,"score_gpt":0.638879658298733,"score_spread":0.1224128694868789,"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."}}