THE MAKING AND UNMAKING OF AFRICAN LANGUAGES: ORAL COMMUNITIES AND COMPETITIVE LINGUISTIC WORK IN WESTERN KENYA
Bibliographic record
Abstract
ABSTRACT This article examines the history of efforts to create a standard written language in western Kenya. In the 1940s, the Luyia Language Committee worked to standardise one Luyia language out of a set of diverse, distinct, and yet mutually intelligible linguistic cultures. While missionaries worked to imbue translations with ideals of Christian discipline, domestic virtue, and civilisation, local cultural entrepreneurs took up linguistic work to debate morality, to further their political agendas, and to unite their constituents. Rather than subsume linguistic difference, these efforts at standardisation reveal the dynamism of oral communities, and how they encouraged a culture of competitive linguistic work. Examination of these efforts challenges previous historians' insistence on the role of linguistic consolidation in the making and unmaking of political communities in colonial Africa.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".