Bibliographic record
Abstract
* Preface by Sangeeta Kamat * Introduction - NGOization: Complicity, Contradictions and Prospects - Aziz Choudry and Dip Kapoor * 1. Saving Biodiversity, for Whom and for What? Conservation NGOs, Complicity, Colonialism and Conquest in an Era of Capitalist Globalization - Aziz Choudry * 2. Social Action and NGOization in Contexts of Development Dispossession in Rural India: Explorations into the Un-civility of Civil Society - Dip Kapoor * 3. NGOs, Indigenous Peoples and the United Nations - Sharon H. Venne * 4. From Radical Movement to Conservative NGO and Back Again? A Case Study of the Democratic Left Front in South Africa - Luke Sinwell * 5. Philippine NGOs: Defusing Dissent, Spurring Change - Sonny Africa * 6. Disaster Relief, NGO-led Humanitarianism and the Reconfiguration of Spatial Relations in Tamil Nadu - Raja Swamy * 7. Seven Theses on Neobalkanism and NGOization in Transitional Serbia - Tamara Vukov * 8. Peace-building and Violence against Women: Tracking the Ruling Relations of Aid in a Women's Development NGO in Kyrgyzstan - Elena Kim and Marie Campbell * 9. Alignment and Autonomy: Food Systems in Canada - Brewster Kneen
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.005 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.006 |
| Insufficient payload (model declined to judge) | 0.012 | 0.003 |
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".