Instances of Gradual Vocabulary Loss in Yoruba: A Need for Documentation
Bibliographic record
Abstract
A careful scrutiny of the use of Yoruba in contemporary discourse at various social situations reveals that there are two vital aspects of its system of communication which are gradually, and quite imperceptibly, creeping out. These are idioms and proverbs, two indispensable pillars of Yoruba communication system. However, in contrast with the trend in the ancient past, idiomatic and proverbial expressions are no longer salient in Yoruba media of communication such as verbal discourse, written materials, home videos, audio recitals, just to mention but a few. This clearly shows that these aspects of the language are endangered. This paper therefore highlights some of the Yoruba idioms and proverbs that are seldom used in today’s discourse and discusses some of the ensuing social, cultural, religious and linguistic implications of such anomaly. To that effect, the paper then concludes by advocating a need for intra-lingual documentation of these expressions as a proactive measure aimed at ensuring their potential revitalization should they eventually die out of the language in the process of time.
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 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 | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".