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Record W2161194188 · doi:10.1177/0261927x02021003003

Understanding Irony

2002· article· en· W2161194188 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

VenueJournal of Language and Social Psychology · 2002
Typearticle
Languageen
FieldPsychology
TopicLanguage, Metaphor, and Cognition
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsSarcasmPsychologyIronyComprehensionContext (archaeology)LinguisticsCued speechLiteral (mathematical logic)Social psychologyCognitive psychology

Abstract

fetched live from OpenAlex

Katz and Pexman reported that certain occupations (e.g., comedian) were associated with ironic speech and that participants rated metaphors as more sarcastic when speakers were members of such occupations. In the present research, the authors investigated whether speaker occupation was a cue to ironic intent when the statements were not metaphors (e.g., literal statements such as “you are a wonderful friend, ” potentially an ironic insult, and “you are a terrible friend, ”potentially an ironic compliment). Results of Experiments 1 and 2 demonstrated that speaker occupation stereotypes were routinely integrated in the comprehension process but only cued ironic intent when other contextual cues were minimal.Results of Experiment 3 demonstrated that speaker occupation stereotypes involve particular types of information in the context of potentially ironic speech: a speaker’s perceived tendencies to be humorous, to criticize, to be sincere, and also a speaker’s perceived education level.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.183
Threshold uncertainty score0.997

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)0.0040.000

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 head0.112
GPT teacher head0.365
Teacher spread0.253 · 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