{"id":"W4319756424","doi":"10.3390/soc13020042","title":"A Critical Lens on Health: Key Principles of Critical Discourse Analysis and Its Benefits to Anti-Racism in Population Public Health Research","year":2023,"lang":"en","type":"article","venue":"Societies","topic":"Obesity and Health Practices","field":"Health Professions","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Critical discourse analysis; Public health; Sociology; Population health; Critical theory; Social determinants of health; Population; Politics; Public relations; Health policy; Engineering ethics; Political science; Medicine; Ideology","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","sts"],"consensus_categories":[],"category_scores_codex":[0.01178668,0.0001589548,0.0006859797,0.001101771,0.002045363,0.00004096646,0.0001770332,0.0002668102,0.0001350557],"category_scores_gemma":[0.009557267,0.0001521661,0.00007928395,0.002728552,0.0002341713,0.0004992402,0.0002748889,0.001357547,0.0002037606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003461754,"about_ca_system_score_gemma":0.0009527373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002337351,"about_ca_topic_score_gemma":0.01042364,"domain_scores_codex":[0.9928475,0.003266049,0.0009881592,0.0004917591,0.0009306749,0.001475872],"domain_scores_gemma":[0.9913632,0.007095872,0.0001786605,0.0003127872,0.0005140338,0.0005354353],"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":[0.0001005034,0.0008573213,0.3277497,0.00910851,0.00009093941,0.000006504526,0.1201373,0.0001343877,0.00001882927,0.526138,0.0120035,0.003654445],"study_design_scores_gemma":[0.0002568856,0.000450961,0.9578952,0.0006736564,0.00001744857,2.965346e-7,0.03588866,0.0005845857,0.000003166376,0.001851778,0.002248862,0.0001284885],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6502041,0.0008900419,0.00002243008,0.3474753,0.0001906328,0.0006267052,0.0001051173,0.00006713603,0.0004185877],"genre_scores_gemma":[0.9925252,0.002453768,0.0002996346,0.003798402,0.00016425,0.0001267247,0.00005694474,0.00002361299,0.000551464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6301455,"threshold_uncertainty_score":0.9992538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5608980439067386,"score_gpt":0.614926492031761,"score_spread":0.05402844812502239,"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."}}