Language ecology, language endangerment, and relict languages: Case studies from Adamawa (Cameroon-Nigeria)
Bibliographic record
Abstract
Abstract As a contribution to the more general discussion on causes of language endangerment and death, we describe the language ecologies of four related languages (Bà Mambila [mzk]/[mcu], Sombә (Somyev or Kila) [kgt], Oumyari Wawa [www], Njanga (Kwanja) [knp]) of the Cameroon-Nigeria borderland to reach an understanding of the factors and circumstances that have brought two of these languages, Sombә and Njanga, to the brink of extinction; a third, Oumyari, is unstable/eroded, while Bà Mambila is stable. Other related languages of the area, also endangered and in one case extinct, fit into our discussion, though with less focus. We argue that an understanding of the language ecology of a region (or of a given language) leads to an understanding of the vitality of a language. Language ecology seen as a multilayered phenomenon can help explain why the four languages of our case studies have different degrees of vitality. This has implications for how language change is conceptualised: we see multilingualism and change (sometimes including extinction) as normative.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".