International NGOs and National Regulation in an Age of Terrorism
Bibliographic record
Abstract
Abstract This article examines the regulation of international non-governmental organizations (INGOs) in the United States, United Kingdom, Canada, Germany, and Japan to answer two questions. First, to what extent has the domestic institutional context facing INGOs changed following dramatic attacks by transnational terrorists on Western liberal democracies? Second, what effect has new counterterrorism legislation had on the organizational and strategic decisions of INGOs, and thus their locations and operations, since 2001? We argue that formal regulations on non-profits have changed less than expected, given widespread alarm about counterterrorism legislation in non-profit communities around the world. However, a new climate of uncertainty has hampered INGOs ability to adjust appropriately to their new institutional environment. Counterterrorism regulations have thus generated unintended consequences, including inefficiencies, redistribution of resources, and self-censorship that may outweigh the benefits for national security given the limited nature of much of the regulatory change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".