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Record W4409308909 · doi:10.1075/ld.00195.kal

Self-reported irony and psychosocial factors

2025· article· en· W4409308909 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

VenueLanguage and Dialogue · 2025
Typearticle
Languageen
FieldPsychology
TopicHumor Studies and Applications
Canadian institutionsBrock University
Fundersnot available
KeywordsIronyPsychosocialPsychologySocial psychologyPsychotherapistArtLiterature

Abstract

fetched live from OpenAlex

Abstract The current study examines individual differences in self-reported irony use in a sample of 151 young adult females in Poland ( M age = 22.19; SD = 2.17). In addition to self-reported irony use (via the Irony Self-Report Scale, a Polish translation of the Sarcasm Self-Report Scale, SSS, Ivanko et al. 2004 ), we analyzed Big Five personality traits ( Ten-Item Personality Inventory , Gosling et al. 2003 ), humor styles ( The Humor Styles Questionnaire , Martin et al. , 2003 ), and self-reported social media use, frequency of face-to-face interactions, and the number of siblings. Self-reported irony use was partially predicted by the personality trait of agreeableness and by three humor styles — aggressive, self-defeating and self-enhancing. Among the other variables, only the number of siblings proved to be a significant predictor of self-reported irony use. Overall, our results add to the emerging literature on individual differences in irony use.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.014
GPT teacher head0.325
Teacher spread0.311 · 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