{"id":"W2233967282","doi":"10.22584/nr41.2015.004","title":"Addressing Historical Impacts Through Impact and Benefit Agreements and Health Impact Assessment: Why it Matters for Indigenous Well-Being","year":2015,"lang":"en","type":"article","venue":"The Northern Review","topic":"Indigenous Health, Education, and Rights","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"University of Guelph","keywords":"Indigenous; Corporate governance; Health impact assessment; Political science; Poverty; Resource (disambiguation); Environmental planning; Public health; Environmental ethics; Geography; Economic growth; Business; Medicine; Law; Ecology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.003383402,0.0002354162,0.0005163248,0.00004649274,0.004315132,0.0001366454,0.000253937,0.00007941723,0.00004350417],"category_scores_gemma":[0.00001213777,0.0001363422,0.0001235169,0.0002325306,0.0001231176,0.0003382361,0.000006601847,0.0001786403,0.00001246757],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00266051,"about_ca_system_score_gemma":0.00660535,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.270009,"about_ca_topic_score_gemma":0.3961017,"domain_scores_codex":[0.9977146,0.0003248625,0.0004633592,0.0002850749,0.0004294253,0.0007827221],"domain_scores_gemma":[0.9984642,0.0001500528,0.0004451446,0.0002768799,0.0001766109,0.0004871413],"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":[0.00003103103,0.0002067612,0.03308156,0.002598104,0.0001785715,0.000002701955,0.926396,0.000006545277,7.563259e-7,0.001683013,0.01172994,0.02408504],"study_design_scores_gemma":[0.0004933156,0.000461403,0.007593374,0.002110751,0.0001351432,0.0000243994,0.002659286,0.000004959402,8.897779e-7,0.005777741,0.9804015,0.0003371921],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"review","genre_scores_codex":[0.5133229,0.4056271,0.0004892377,0.05984636,0.001031166,0.007709005,0.00003874991,0.0001133037,0.01182211],"genre_scores_gemma":[0.1826608,0.7957131,0.001102618,0.01597862,0.001335677,0.00005510066,0.00008287441,0.0001060765,0.002965132],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.9686716,"threshold_uncertainty_score":0.9990263,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1077702823411352,"score_gpt":0.4387154698777155,"score_spread":0.3309451875365803,"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."}}