The Uptake of Critical Perspectives in the Field of Global Mental Health: A Critical Interpretive Synthesis
Bibliographic record
Abstract
Abstract An emancipatory movement is surging within the of global mental health (GMH) field, advancing the groundwork laid by scholars who champion a more critical, self-reflective, decolonized, and socially responsive discipline. As GMH enters its second decade, there have been numerous critiques of its origins and underlying paradigms, with increasing emphasis on critical approaches in recent publications. However, there is no comprehensive synthesis has yet been undertaken to understand how critical perspectives have been integrated into the GMH literature. To contribute to the ongoing discourse aimed at cultivating GMH as a critical and socially responsive discipline, this article employed the critical interpretive synthesis method. critical interpretive synthesis is designed to navigate the synthesis of extensive and diverse literature while actively engaging with the foundational assumptions that shape and inform the body of research via employing a critical lens to scrutinize the data. We conducted searches using PubMed, MEDLINE(OVID), PsycINFO, Scopus and EMBASE data bases; published between 2007 and February 2023. We included 58 articles that have embraced critical perspectives, whether explicitly or implicitly. Through this iterative process, five distinct themes or “four turns” emerge: (1) the inward turn, focusing on the “local” as a source of alterity, resistance, and critique; (2) turning the critical lens outward or political turn; (3) the push for a broader agenda; and (4) the reflexive turn. This article discusses the implications of four “turns” in how critical perspectives have been and are being used, in relation to the goal of developing as a socially responsive discipline.
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 | 0.221 | 0.289 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.031 | 0.023 |
| Science and technology studies | 0.010 | 0.032 |
| Scholarly communication | 0.029 | 0.023 |
| Open science | 0.004 | 0.014 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".