The Potential And Limits Of Mobile Phone Usage For Development In Africa: Innovation And Top-Down-Meets-Bottom-Up Partnering
Bibliographic record
Abstract
The African continent currently boasts the highest mobile telephony growth rates in the world, bringing new communications possibilities to millions of people. The potential for mobile phones to reach a large and growing base of users across the continent, and be used for development-related purposes, is becoming widely recognized, evidenced by the growing number of development-oriented projects, applications, and programs that specifically make use of mobiles. Pent up demand and limited resources have led to innovative usage and services being developed at the grassroots level. Yet much remains to be done by governments in order to support further growth of telecommunications markets and services, while the private sector, non-profits, and academics all have an important role to play in the development process as well. The phenomenon of top-down-meeting-bottom up partnerships that are springing up across the continent offers the potential for cultivating the necessary feedback loops between various actors involved in the development process, in order to create relevant applications that meet real needs.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".