Bibliographic record
Abstract
The data for this study was extracted from the quarterly edition of Our Daily Bread (December 2007, January, February 2008) owing to its graphological layout. The aim of the study is to examine how a major stylistic meaning inducing technique in text composition manifests at the graphological level. John 3:16 in this devotional edition had been re-arranged by Anne Cetas to carry a lot of stylistic significance. The graphological study of this text featured the use of gothic printed letters, re-arrangement (verse paragraph), capitalization, and punctuation marks. Gothic printed and capitalization were graphically fussed together to coin VALENTINE out of this verse of the Scripture. Speech acts, presupposition, inference, implicature and mutual contextual beliefs (MCBs) were used to interpret the meaning of the text.The present analysis has widened the scope of knowledge in the area of stylistics and even that of pragmatics. The graphic representation of John 3:16 and the obvious images contained in it are a clear testimony to the fact that stylistics study and practice could be more than an academic gymnastics. The study validates the thesis which states that both style/form and context contribute in equal measure to any knowledge gained in the course of reading a text.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".