Bibliographic record
Abstract
From September to December 2009 I conducted interviews with different actors in the field ofcommunity radio in Dakar, Senegal. These actors included practitioners or journalists, technicians and directors, consultants, trainers and project managers in NGOs specialized in media development, and civil servants from major governmental regulations institutions. Although the research literature on radio for development tends to focus on rural radio stations, I chose to focus on stations in Dakar because their urban location and physical proximity to international actors confer on them a front-line role, exacerbating the forces affecting their activity. The region of Dakar, the capital of Senegal, accounts for approximately 20 percent of the country’s population. It kept its place as the regional (West African) capital from the colonial era, housing many transnational organizations, NGOs, and cooperation agencies’ main quarters/offices and concentrating most of the country’s economic activity (United Nations 2007). Through this research I discovered that the strong presence of international developmentactors poses a significant difference between the workings of community radio in Dakar versusthe North American context.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".