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Record W2040555246 · doi:10.1080/0163853x.2010.532757

When Sarcasm Stings

2011· article· en· W2040555246 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

VenueDiscourse Processes · 2011
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsWestern University
Fundersnot available
KeywordsSarcasmAggressionPsychologyPerspective (graphical)Negativity effectSocial psychologyArgument (complex analysis)Statement (logic)Cognitive psychologyComputer scienceIronyLinguisticsArtificial intelligence

Abstract

fetched live from OpenAlex

The use of sarcasm sometimes lessens and sometimes enhances the negativity inherent in a sarcastic statement. Using a realistic conversational format, participants read either a sarcastic or a non-sarcastic aggressive argument between same-gendered interlocutors, and rated the pragmatic goals being expressed using a range of measures taken from previous studies. A factor analysis meaningfully grouped the dependent variables into separate factors, one of which indexed “victimization” and a second of which indexed “relational aggression.” The sarcastic version was perceived as more victimizing and more relationally aggressive, contrary to the muting hypothesis. Secondary analyses demonstrated that participants perceived the negative comment of the aggressor as more humorous and less aggressive when taking the perspective of the aggressor than when taking the perspective of the victim, and that male participants reported greater use of sarcasm in everyday life, but did not produce more when given the opportunity to do so.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.632
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0080.001

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 head0.049
GPT teacher head0.326
Teacher spread0.277 · 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