Bibliographic record
Abstract
Previous studies on J.P. Clark-Bekederemo’s poetry have concentrated on literary and some linguistic features, highlighting the nexus between theme and figuration in the works. However, such studies have not paid attention to the role deictics play in foregrounding stylistic functions in the texts, which is absolutely essential for a comprehensive description and interpretation of the poet’s idiolect. This study, therefore, investigates the stylistic value of deictic words in encoding or reinforcing aspects of meaning and aesthetics in the poetry under study. Specifically, with M.A.K. Halliday’s systemic functional linguistics as the analytical platform, the study demonstrates that the deployment of personal pronouns ‘I,’ ‘we’, ‘us’ and ‘me’; locative adverbs ‘here’, ‘there/elsewhere’ and temporal adverbs ‘now’ and ‘then’, helps the poet to relate his experiences, visions and propositions within specific spatial or temporal frameworks. The aim is to show that lexico-grammatical patterns of language use such as deictics have the potentials to combine with other elements of language to convey textual message and also achieve artistic beauty.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".