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Record W4404877463 · doi:10.1075/pc.24039.olk

Training studies provide new insights about mechanisms of irony development

2024· preprint· en· W4404877463 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePragmatics & Cognition · 2024
Typepreprint
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsWestern University
Fundersnot available
KeywordsIronyTraining (meteorology)PsychologyArtLiteratureGeography

Abstract

fetched live from OpenAlex

Abstract In verbal irony, there is a contrast between the literal meaning of what is stated and the intended meaning of the words. As successful comprehension of irony requires going beyond lexical meaning, the ability to understand it tends to develop late compared to literal language and it is challenging for children. Numerous explanations have been proposed for the late development of irony comprehension, including emerging language and perspective-taking skills, working memory, and metapragmatic knowledge. Irony training studies have the potential to be an effective means of testing these explanations and moving beyond correlational designs. We review recent studies that tested this possibility. The results suggest that even short-term irony training can be effective for improving children’s irony comprehension accuracy, and that metapragmatic knowledge is a key mechanism of irony understanding. We outline directions for future training studies and link those to possibilities for both intervention and theory development.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.094
GPT teacher head0.353
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it