Transitivity Analysis of Proverbs in Achebe’s A Man of the People
Bibliographic record
Abstract
The language of literary texts is adorned with proverbs, a cultural element which to some extent has become significant in the growth and development of African literature and in the portrayal of meaning assigned by the writer. This paper explores the relationship between linguistic structures and culturally constructed meaning in Chinua Achebe’s novel A Man of the people by critically examining the transitivity of proverbs used in the work. This study is anchored on Halliday’s Systemic Functional Grammar. The analysis reveals that Achebe uses more material processes, followed by mental processes and then relational and verbal processes. Furthermore, the types of transitivity process, participants, circumstatials contribute towards the construction of themes reflected in the novel. Based on the results, the paper concludes that Achebe uses a variety of transitivity processes as proposed by M.A.K. Halliday with the exception of existential and behaviour. He uses actors, sensers, carriers, identifiers, to convey message of his novel. Achebe mostly uses circumstances of extent, location, and manner to show that the actions take place in a certain place, time, and at a certain frequency. The paper concludes that Achebe’s use of varieties of processes, participants and circumstances has made his novel interesting and readable.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.010 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".