Pragmatic roles in Wole Soyinka’s The Trials of Brother Jero and Jero’s Metamorphosis
Bibliographic record
Abstract
Performance of role is central to the understanding of any discourse or activity because, through it, the implicit meaning is made obvious. Previous studies have considered the role of context in understanding interaction or discourse but they have neglected pragmatic roles in the understanding of any discourse, especially literary discourse. Thus, this study, therefore, examines how pragmatic role contributes significantly to the understanding of discourse and how it reveals participants’ intentions in Wole Soyinka’s The Trials of Brother Jero and Jero’s Metamorphosis. The study adopts Jacob Mey’s 2001 Pragmatic act theory. Data were sourced from relevant utterances in the text and were subjected to pragmatic analysis. Two broad categories of roles: social-informed and religious-informed roles, characterised Wole Soyinka’s The Trials of Brother Jero and Jero’s Metamorphosis . Social-informed role divides into a deceiver, debtor and creditor roles; while religious-informed role splits into prophet, discipler and disciple roles. Denying, forecasting, impersonating, lying, insisting, predicting, instructing and submitting are various practs used to foreground these roles. The paper concludes that studying various pragmatic roles in any discourse will not only contribute to the understanding of the discourse but will also reveal the interactants’ covert intentions.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.023 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".