Bibliographic record
Abstract
Abstract This article reviews the incongruity, the superiority, and the relief theories of humour. Challenging the dominant notion of humour as a coping mechanism, it explores humour’s potential for positive transformation. It investigates the uses of humour in Nigeria, including its social and even unsuspected psychological functions. It also inquires into the problem of a seeming rising incidence of unhappiness among Nigerians despite their much-vaunted humorous nature and despite the relief theory of humour being the dominant perspective in humour studies. By spotlighting the synergy of activism and art in humour, subliminal tendencies, and Nigerians’ distinct comic intelligence, the article attempts a nuanced analysis of the production and consumption of humour, with an accent on the growing activist-oriented humour on social media platforms, particularly Twitter. In contrast to traditional stand-up comedy, this activist-oriented humour is found to be generally geared towards real-time impact through a combined deployment of words and actions. The research puts forward illustrative examples of how social media humour has surpassed other more orthodox comedic practices and thereby engendered remarkable social and political impacts in Nigeria.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.024 | 0.008 |
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".