Emotional Consistency as Evidence of Dynamic Equivalence among English Translations of the Bible
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In order to be dynamically equivalent, different translations of the same text must have the same effects (including emotional effects) on an audience. In this research, six English translations of the Bible (four entire Bibles, one Tanakh, and one nearly complete translation) were scored with the Dictionary of Affect in Language, which quantifies the Pleasant, Active, and Imaging undertones of words, and were compared in terms of these undertones. In spite of small differences among them (translations into simpler modern English were significantly more Pleasant, Active, and Concrete), the translations were emotionally consistent and therefore dynamically equivalent to one another with respect to emotion and imagery. The median correlation among translations for Pleasantness, Activation, and Imagery was .9. The greatest variation in scores was associated with chapters. Emotional and imagery differences between books and chapters of the Bible are described and discussed.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it