Decolonizing global health: A scoping review protocol
Bibliographic record
Abstract
Abstract Although there has been attention paid to decolonizing global health, there is no accepted understanding of the concept. Therefore, this protocol outlines the steps for a planned scoping review to assess the academic literature for discussions on decolonizing global health. Namely, to consider what this concept means within mainstream global health databases and how it can be acted on. We also hope to shed light on who is participating in these discussions. The PRISMA guidelines for Scoping Reviews (PRISMA‐ScR) was used to develop this scoping review protocol. With the guidance of an academic librarian, we searched OVID Medline, OVID Embase, EBSCO CINAHL Plus, Web of Science, PAIS Index, Worldwide Political Science Abstracts, and the International Bibliography of the Social Sciences databases from inception to the date the search is conducted. The inclusion criterion is that texts must: (i) use the exact phrasing of “decoloni* global health” or “anticolonial global health,” (ii) include substantive discussion of what decolonizi* global health or anticolonial global health means (i.e., we will exclude single mentions that do not include an explanation, elaboration, or context), and (iii) be published in English. Similarly, the exclusion criteria include: (i) texts that do not substantively discuss decolonizing global health and (ii) grey literature hits. This protocol establishes the study parameters for the planned scoping review. We anticipate the findings from the scoping review to bring much needed clarity to discussions around decolonizing global health, in terms of meaning(s), gaps, and possible actions.
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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 | 0.255 | 0.232 |
| Meta-epidemiology (narrow) | 0.005 | 0.008 |
| Meta-epidemiology (broad) | 0.009 | 0.012 |
| Bibliometrics | 0.020 | 0.016 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.015 | 0.013 |
| Insufficient payload (model declined to judge) | 0.112 | 0.034 |
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".