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Record W1988158129 · doi:10.1177/0261927x09335253

“Should Be Fun—Not!”

2009· article· en· W1988158129 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 · 2009
Typearticle
Languageen
FieldComputer Science
TopicDigital Communication and Language
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHyperboleSarcasmStatement (logic)PsychologyComprehensionLinguisticsEllipsis (linguistics)IronyMetaphor

Abstract

fetched live from OpenAlex

According to Kreuz's principle of inferability, speakers tend to employ nonliteral language when it can reasonably be perceived by their conversational partner. In a computer-mediated communicative setting, such as e-mail, this suggests that the e-mail writer might use discourse tools that facilitate comprehension on the part of the recipient. The present study examined rates of usage for various forms of nonliteral language in 210 e-mail messages written by young adults. In 94.30% of all e-mails there was at least one nonliteral statement, and participants used an average of 2.90 nonliteral statements per e-mail. Results showed that forms of nonliteral language that are typically deemed to be riskier, such as sarcasm, were used much less frequently than other less risky forms, such as hyperbole, and were marked with discourse markers more often. This indicates that e-mail authors are sensitive to the risky nature of nonliteral language use in e-mail, yet are savvy to the tools available to them in this communicative medium.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.770
Threshold uncertainty score0.214

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 science0.0010.000
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 head0.060
GPT teacher head0.388
Teacher spread0.329 · 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