Diversity, Equity, and Inclusion for Peace? Making Visible Epistemic Exceptionalism in Peacebuilding Discourse
Bibliographic record
Abstract
The murder of George Floyd on 25 May 2020, at the hands of a Minnesota police officer in the United States propelled social justice-related discourses and the normative agenda of Diversity, Equity and Inclusion (DEI) to the fore in media, academia, and popular culture. Even during a heightened moment of structural violence, Global North peacebuilding institutions located in Turtle Island (North America) remained largely silent in critical debates around the potentials and limits of DEI in confronting structural oppression in its own context, while promoting ‘inclusive peace’ in conflicts located in the Global South. This article problematizes this dynamic, drawing on decolonial theories in IR and peace studies to signal the tension between DEI literature and decolonial theory to develop the concept of epistemic exceptionalism that makes visible the bypassing of coloniality within peace studies and its production of knowledge. It argues that critically relating DEI to peacebuilding discourse (beyond a performative box-ticking exercise) creates the emancipatory potential to reframe and address structural conflicts in the Global North.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.077 |
| Scholarly communication | 0.016 | 0.024 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.003 | 0.006 |
| 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; 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".