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Record W4402816728 · doi:10.3390/soc14090186

Cross-Disciplinary Rapid Scoping Review of Structural Racial and Caste Discrimination Associated with Population Health Disparities in the 21st Century

2024· article· en· W4402816728 on OpenAlex
Drona Rasali, Brendan M. Woodruff, Fatima A. Alzyoud, Daniel Kiel, Katharine Traylor Schaffzin, William Osei, Chandra L. Ford, Shanthi Johnson

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSocieties · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicRacial and Ethnic Identity Research
Canadian institutionsBC Centre for Disease ControlUniversity of WindsorBritish Columbia Institute of TechnologyUniversity of British Columbia
Fundersnot available
KeywordsCasteHealth equityDisciplinePopulationCross disciplinarySociologyGeographyPolitical scienceDemographyEconomic growthSocial scienceData scienceHealth careEconomicsComputer science

Abstract

fetched live from OpenAlex

A cross-disciplinary rapid scoping review was carried out, generally following the PRISMA-SCR protocol to examine historical racial and caste-based discrimination as structural determinants of health disparities in the 21st century. We selected 48 peer-reviewed full-text articles available from the University of Memphis Libraries database search, focusing on three selected case-study countries: the United States (US), Canada, and Nepal. The authors read each article, extracted highlights, and tabulated the thematic contents on structural health disparities attributed to racism or casteism. The results link historical racism/casteism to health disparities occurring in Black and African American, Native American, and other ethnic groups in the US; in Indigenous peoples and other visible minorities in Canada; and in the Dalits of Nepal, a population racialized by caste, grounded on at least four foundational theories explaining structural determinants of health disparities. The evidence from the literature indicates that genetic variations and biological differences (e.g., disease prevalence) occur within and between races/castes for various reasons (e.g., random gene mutations, geographic isolation, and endogamy). However, historical races/castes as socio-cultural constructs have no inherently exclusive basis of biological differences. Disregarding genetic discrimination based on pseudo-scientific theories, genetic testing is a valuable scientific means to achieve the better health of the populations. Epigenetic changes (e.g., weathering—the early aging of racialized women) due to the DNA methylation of genes among racialized populations are markers of intergenerational trauma due to racial/caste discrimination. Likewise, chronic stresses resulting from intergenerational racial/caste discrimination cause an “allostatic load”, characterized by an imbalance of neuronal and hormonal dysfunction, leading to occurrences of chronic diseases (e.g., hypertension, diabetes, and mental health) at disproportionate rates among racialized populations. Major areas identified for reparative policy changes and interventions for eliminating the health impacts of racism/casteism include areas of issues on health disparity research, organizational structures, programs and processes, racial justice in population health, cultural trauma, equitable healthcare system, and genetic discrimination.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.640
Threshold uncertainty score0.646

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.060
GPT teacher head0.438
Teacher spread0.378 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it