INGO memberships revisited: Local variation of receptor sites in the education sector
Bibliographic record
Abstract
This article investigates cross-national variation in the types of locally based actors, or “receptor sites,” that connect with international non-governmental organizations (INGOs) in local contexts. Empirics center on an INGO disseminating global best practices for education in humanitarian crises to a membership of around 10,000 individuals in over 150 countries. Members reported working at a range of organizations, here conceptualized as receptor sites. Using multivariate regression, I examine cross-national differences in a subset of these workplace affiliations. Findings show that members join primarily in Western countries and in specific sites of humanitarian crises. However, they tend to be affiliated with different types of receptors in these two contexts due to differences in the underlying factors that generate INGO ties. Receptors influential in the construction of global norms (such as aid donors and universities) dominate in the Western core, where ties serve as a means for promoting cultural ideals elsewhere. In contrast, implementing organizations (such as local schools, non-governmental organizations (NGOs), and governments) prevail in humanitarian crises, where ties offer access to global resources in tackling local issues. Country-level ties to INGOs are thus not always equivalent, but can capture locally variant pathways for diffusion.
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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 | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".