Bibliographic record
Abstract
Abstract This article explores ways of decolonising Development Studies by: (1) examining the discipline’s tendencies towards what some have called ‘imperial amnesia’, that is, proclivities towards disavowing if not erasing European colonialism, most evident in 1950s–1960s Modernisation theory, but also more recently in the work of such analysts as Bruce Gilley and Nigel Biggar; (2) considering the opportunities and perils of ‘epistemic decolonisation’, that is, ways of decolonising knowledge production in the discipline, including the limits of ‘non-Eurocentric’ pedagogies; and (3) reflecting on forms of material decolonisation (e.g., the reduction of socioeconomic inequalities by improving better access to education or resisting the corporatisation of publicly funded research) that need to accompany any epistemic decolonisation for the latter to be meaningful.
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 | 0.032 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".