Gender Mainstreaming in a Development Project: Intersectionality in a Post‐Colonial Un‐doing?
Bibliographic record
Abstract
This article explores some critical reflections engaged in as part of the earliest stages of applying for an international development project grant. Though most of the funding came from the North, which had the potential to reproduce typical North–South relations, both parties involved in the project agreed to predicate relationships on principles of equity in an attempt to decolonize relationships, or what could be seen as a sort of ‘un‐doing’ of traditional colonial relations. Tensions emanating from within and among the teams at early meetings underscored the complexity of un‐doing colonial relationships, as well as the way that colonial relations awkwardly but seamlessly intersect with gendered, classed and heteronormative individual and organizational relations. It also highlights the messiness and difficulty in transform(ing) hegemonic social conditions in a single international institution or project.
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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 | 0.034 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.044 | 0.081 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.002 | 0.025 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".