Bibliographic record
Abstract
The title of Sarah Michael's Undermining Development: The Absence of Power among Local NGOs in Africa accurately describes both her thesis and her principal concerns. The study, which compares development related, nongovernmental organizations in sub-Saharan Africa with their counterparts in Asia and Latin America, serves Michael's primary purpose, which is to identify strategies that will empower local African organizations. In this regard, Michael's research reflects the realities that face the international development community, and it points to adjustments that are needed generally to support local organizations' efforts to achieve sustainability. Michael contends that the lack of power that characterizes indigenous nongovernmental organizations in sub-Saharan Africa is one of the primary factors undermining development in Africa. This powerlessness can be correlated with the overall state of underdevelopment on the continent. Michael is interested in knowing why African nongovernmental organizations have not succeeded in positioning themselves as powerful instruments for development given that some of their counterparts in Asia and Latin America have been able to shift the balance of power in their favor. She goes beyond the traditional rhetoric that points to the flaws of African organizations. In particular, she examines the evolution and the environmental factors that have been conducive to the empowerment of Asian and Latin American groups. This analysis becomes her frame of reference for helping indigenous African organizations appropriate more power for themselves.
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.
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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.008 | 0.020 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".