The socio-rhetorical force of ‘truth talk’ and lies: The case of 1 John
Bibliographic record
Abstract
This article canvassed Greek and Roman sources for discussions concerning truth talk and lies. It has investigated what social historians and/or anthropologists are saying about truth talking and lying and has developed a model that will examine the issue of truth and lying in socio-religious terms as defined by the Graeco-Roman sources. The article tracked down the socio-rhetorical force of truth talk and lies, in terms of how they are strategically deployed to negotiate authority, to exert epistemic control, to define a personal and communal identity and to defend innovation in the midst of competing truth claims. It focused on the New Testament writing (1 John) and demonstrated that the author, in his desire to establish and defend his vision of truth, resorts to a style of truth talk endemic to the literary habits of Graeco-Roman antiquity. In so doing, the author established himself as a credible witness, set himself apart from those propounding falsehoods and, to some extent, distanced himself from the vision of truth propounded in the Gospel of John.
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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.076 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.006 | 0.008 |
| 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".