Title Sociolinguistic Analysis of some Akan proverbs
Bibliographic record
Abstract
This study examined the sociolinguistic analysis of some Akan proverbs. With this, the analysis predicated on the social contexts that bring about the use of the proverbs and their sociolinguistic implications. The data sourced from the research participants were analysed alongside Dell Hymes’ (1974) “Ethnography of Communication”, which also served as the theoretical framework that underpinned the study. In all, twenty one (p.21) proverbs were analysed which saw the various factors of communication, as postulated by Hymes (1974) coming to bear. Discussing the analysis, it was indicated that the home is the place where proverbs are mostly used. The time for the use of proverbs also saw the evening dominating in the data analysis. With the addressers under participants, men were found to be the people who mostly use proverbs in the Akan society. Anybody, be it a man, woman or child in the Akan society, qualifies to be addressed with proverbs, per the analysis in this study. The end of the use of Akan proverbs is to encourage, rebuke, admonish and warn the addressee. Finally, the key, which also manifests as the tone under which a particular proverb is used saw serious tone as the most frequently used tone in the analysis, as most Akan proverbs are used to direct the paths of its members, whenever they go wayward.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".