Pop-up non-governmental organizations: (Re)producing colonial helping relations
Bibliographic record
Abstract
This qualitative study engages a postcolonial lens to examine the (re)production and disruption of neocolonial, racist power relations in Pop-Up Non-Governmental Organizations’ (PUNs) transnational helping relationships. Recognizing the historical and contemporary use of representations to further colonizing, racist goals, the analysis examines the use of text-based self-representations and refugee representations. This study utilizes five critical discourse analysis tools on four PUN websites’ texts through which the PUNs self-describe, share their work, and seek support. In analyzing these websites, this research aims to identify how the four PUNs navigate the inherent power imbalance between their Northern organizations and the Southern refugees they seek to support. Ultimately, the analysis presents evidence that, although the four PUNs endeavour to disrupt colonial practices, the websites’ representational practices (re)produce colonial, racialized helping relations. It is hoped that this research will support others working from White, Northern perspectives to reflect on their approach and consider alternatives.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| 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".