Seeing like a donor: the unintended harms of rendering civil society legible
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Following the Grand Bargain, there has been increasing focus on aid localisation and partnerships between international and local aid agencies. Yet there has been less scholarly attention on how and why international agency policies and partnerships can cause unintended harm to civil society organisations and their staff. Drawing on James Scott’s seminal work Seeing like a State, and interviews with Myanmar civil society organisation leaders in 2023, this article argues that international agencies often attempt to render civil society “legible” through processes of systematisation and codification. However, these processes can in turn sideline accrued experiential and contextual knowledge, or metis, which is necessary for local organisations’ survival, especially in times of instability. The article highlights several instances in Myanmar where the marginalisation of this more contextual knowledge results in unintended harms. The article concludes that international agencies’ acknowledgement of metis is a crucial and yet still under-recognised pillar of aid localisation.
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.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it