Bibliographic record
Abstract
Abstract The study addresses two problems with recent psycholinguistic research on why people don’t say what they mean, (1) possible underrepresentation in research studies of types of figurative language found in everyday talk, and (2) potential ecological validity problems due to using standard psycholinguistic experimental methodologies and inauthentic language materials. In three experiments, these problems were addressed using authentic productions of a relatively unexplored figurative language type – formulaic language, specifically gratitude acknowledgements , which cover a range of figurativity (e.g., “don’t worry about it”, through, “anytime”), often using hyperbole as part of their functioning – a key focus of the present study. The results demonstrate that speakers use figurative gratitude acknowledgements to achieve the pragmatic effects of politeness and esteem display as well as fondness expression, which are not achieved to the same extents by nonfigurative gratitude acknowledgements. The particular pragmatics of this figurative form, the influence of these pragmatic effects on some theoretical questions, and the broader implications of inclusion of new figurative language forms, as well as authentic language items and methods, in research on figurative language production and pragmatics, are discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".