Decolonizing International Relations and Development Studies: What’s in a buzzword?
Bibliographic record
Abstract
Over the past decade, there has been a new “decolonial turn,” albeit less related than before to land and political independence. “To decolonize” is now associated with something less tangible and often under-defined. We argue that scholars, especially Western ones, should avoid depoliticizing the expression “decolonizing” by using it as a buzzword. Scholars and policymakers should use the expression only if it is closely related to the political meaning ascribed to it by Global South and Indigenous activists and scholars. Decoloniality is a political project of human emancipation through collective struggles, entailing at least the following: 1) abolishing racial hierarchies within the hetero-patriarchal and capitalist world order, 2) dismantling the geopolitics of knowledge production, and 3) rehumanizing our relationships with Others and nature. We conclude that there is a need for epistemic humility and that Western scholars and institutions must refrain from using the word too freely.
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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 | 0.041 | 0.070 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.006 | 0.012 |
| Science and technology studies | 0.014 | 0.074 |
| Scholarly communication | 0.040 | 0.054 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.016 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".