The power of the tongue: Inherent labeling of persons with disabilities in proverbs of the Akan people of Ghana
Bibliographic record
Abstract
Proverbs are an important feature of any language worldwide. In Africa, for instance, people in their everyday conversations use proverbs to add special effects and flavour. However, the inclusion of proverbs in speech goes beyond mere decoration. As a repository of African knowledge and culture, proverbs serve as a medium for educating present and future generations about society’s cultural values, beliefs, and ethics. In this powerful role, proverbs may have significant effects on speakers and their listeners. While these effects may be positive, in terms of their references to certain groups of people, proverbs may have telling effects. In this paper, we examined samples of Ghanaian Akan proverbs on mental and physical disabilities and their meanings, using critical discourse analysis and guided by labeling theory. We conclude that Akan proverbs predominantly label people with disabilities negatively, thereby leading to their stigmatization, marginalization, and exclusion. We recommend using proverbs with negative connotations for people with disabilities as a tool to educate society on how not to treat people with disabilities.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 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".