Promoting Local Languages in Ugandan Primary Schools: The Community as Stakeholder
Bibliographic record
Abstract
Abstract: The community is an important stakeholder in language education, and community views are critical for the successful implementation of new language policies. This article reports on a study on multilingual language policies conducted in two primary schools in two communities in eastern Uganda, one rural and one urban, from 2005 through 2006. The study focused on community responses to the new language education policy, which promotes the teaching of local languages in the first four years of schooling, using questionnaires, individual interviews, and focus-group discussions to collect data from the two communities, each linked to a local primary school. The findings show that in both communities, although participants were generally aware of the new local-language policy, they were ambivalent about its implementation in their school. They recognized the importance of local languages in promoting identity and cultural maintenance, but a higher priority was their children's upward mobility and the desire to be part of wider and more international communities. Further, while area languages such as Luganda and regional languages such as Kiswahili were perceived to have some benefits as languages of wider communication, it was English that received unequivocal support from both communities. The study concludes that parents and communities need to be better informed about the pedagogical advantages of instruction in the local language and that communities need convincing evidence that the promotion of local languages will not compromise desires for global citizenship.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".