Challenges and Opportunities for Psychological Research in the Majority World
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.
Bibliographic record
Abstract
How can psychology transform itself into an inclusive science that engages with the rich cultural diversity of humanity? How can we strive towards a broader and deeper understanding of human behavior that is both generalizable across populations and attentive to its diversity? To address these major questions of our field, relying on scholars from different world regions, we outline first the opportunities associated with conducting psychological research in these and other majority world regions, highlighting international collaborations. Cross-cutting research themes in psychological research in the majority world are presented along with the urgent need to adopt a more critical lens to research and knowledge production within psychology. Indigenization, critical, transformative and liberatory approaches to understanding psychological phenomena framed within the decolonial imperative are presented as future options for a more diverse and equitable psychological science. Next, we address challenges, including limited institutional research infrastructure, limited national investment in research, political and social challenges these regions face, and the impact of imported (rather than locally produced) psychological knowledge. We conclude by offering recommendations to enable psychological science to be more representative of the world’s population. Our aim is to facilitate a broader, better-informed, and more empathic conversation among psychological scientists worldwide about ways to make psychological science more representative, culturally informed and inclusive.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it