Boys Are Boys: A Contrastive Study of Nominal Tautology Between L1 English and L1 Arabic
Bibliographic record
Abstract
This study aims to examine nominal tautology functioned as human nature based on the assumptions by Wierzbicka (1987). It compares English and Arabic tautology on construction like Boys are boys. This study integrates Miki’s evocation function with two other core concepts namely a macro-frame and a micro-frame. In addition, the role of the context is closely investigated as it forms an essential component in the realization of nominal tautology as proposed by Gibbs and McCarrell (1990). All these notions are merged into one solid framework to comprehend the mechanism of tautology in the brain of the speakers/hearer in any given language. Acceptability Judgment Task is used as an instrument to elicit participants’ acceptable judgments and interpretations on human nature tautology. The study includes two groups; English native speakers (51 participants) and Arabic native speakers (34 participants). According to the analyses, the results show no difference between the study groups, in the realization of nominal tautology related to human nature at the level of the acceptability and the interpretation.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".