At the Risk of Not Being Decolonial Enough
Bibliographic record
Abstract
Market-based approaches feature development interventions designed to enable poor people in the Global South to benefit from markets. Decolonial approaches criticize these Western-based interventions in marginalized settings by challenging the implicit assumption that good intentions lead to good outcomes. Despite the many well-founded issues with market-based approaches, as researchers working in this field, we believe we have resources and a privileged platform to make a difference in shaping the ways these interventions take place. We propose a framework distinguishing different approaches to research on market-based interventions that build on two key practices: reflexivity and engagement with local actors. Particularly, we put forward the concept of reflexive pragmatism, which combines strong engagement with local actors and deep reflexivity to produce long-lasting impacts that meet the needs of the poor. Based on our own research experience and the papers in this volume, we suggest ideas for how researchers can consciously strive to decolonize market-based interventions while, at the same time, making their scholarly practices more impactful for communities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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; both teacher heads agree on what is shown here.
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".