The Stylistic Significance of Graphological Devices in Sam Ukala’s Skeletons: A Collection of Stories
Bibliographic record
Abstract
This paper is an investigation of Ukala’s use of graphological devices, and their stylistic functions in his text, Skeletons. In a literary text, language and style are studied at various levels, and the scientific study of language is referred to as linguistics. Although graphology is not a branch of linguistics, its affinity with the phonic substance in particular and language in general, is so close that it exerts considerable influence on style. Therefore, the patterned system of the graphic substance is an aspect of the style of written discourse, which should not be overlooked in the study of the language of a literary text. In this paper, we subject significant graphological devices subsuming italicization, punctuations, and capitalization to practical analysis stylistically. The paper will be of immense contribution to knowledge as it will act as a springboard, to future researchers in the study of the language of African literature
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 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".