One laptop per child: technology, education and development in Rwanda
Bibliographic record
Abstract
This thesis critically examines the One Laptop Per Child (OLPC) organization in the context of Rwanda‘s socioeconomic development plans for the year 2020. OLPC is a relatively new, large-scale development organization dedicated to the improvement of education in the world‘s poorest countries through the distribution of laptops specially designed for children. Rwanda is one of the poorest countries to have signed on the program since its founding in 2005, and ranks in the top five subscribers, having purchased 110,000 laptops for distribution among primary school students. The Government of Rwanda is committed to establishing a middle-income economy on the basis of an information economy, and has adopted OLPC to suit this agenda, while OLPC seeks to focus on the educational aspects of the program. This thesis, in the tradition of the anthropology of development, analyzes the motivations and ideals that guide both OLPC and the Government of Rwanda, and proposes that evaluating the program is better done by understanding it in its local context. This research is based on three months of ethnographic fieldwork in four grade five classrooms in urban Rwanda, along with interviews with key members of OLPC.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".