Definitions, terminology, and related concepts of “racial health equity”: a scoping review protocol
Bibliographic record
Abstract
BACKGROUND: In the USA, access to quality healthcare varies greatly across racial and ethnic groups, resulting in significant health disparities. A new term, "racial health equity" (RHE), is increasingly reported in the medical literature, but there is currently no consensus definition of the term. Additionally, related terms such as "health disparities," "health inequities," and "equality" have been inconsistently used when defining RHE. METHODS: The primary purpose of this scoping review is to investigate the current use and underlying concepts used to define racial health equity. The study will address two key questions: (1) "What terminology and definitions have been used to characterize RHE?" and (2) "What knowledge gaps and challenges are present in the current state of RHE research and theory?" The review will collect and analyze data from three sources: (1) websites from key national and international health organizations, (2) theoretical and narrative published articles, and (3) evidence synthesis studies addressing interventions targeting racial health equity and minority stakeholder engagement. DISCUSSION: Defining "racial health equity" and related terminology is the first step to advancing racial health equity within the USA. This review aims to offer an improved understanding of RHE constructs and definitions, bringing greater unity to national racial health equity research efforts across disciplines. SYSTEMATIC REVIEW REGISTRATION: This protocol is registered with the Open Science Framework at https://osf.io/7pvzq .
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.172 | 0.203 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.026 | 0.024 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.006 | 0.008 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.067 | 0.013 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".