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Record W2060040216 · doi:10.1177/1461445607075349

Lies, rebukes and social norms

2007· article· en· W2060040216 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 Studies · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversité du Québec à Trois-RivièresUniversité Laval
Fundersnot available
KeywordsLyingPsychologySocial psychologyOrder (exchange)Lie detectionDeceptionEpistemologyMedicinePhilosophy

Abstract

fetched live from OpenAlex

Reflecting upon the lies that are tied to rebukes is a fundamental step in the analysis of interactions between health-care professionals and their clients. Our research focuses on questions that incite people to lie, namely, those for which a lying response avoids a rebuke or a judgment based on some type of behaviour. Our objectives are: 1) to characterize the `question/response' exchange that is interpreted as a `potential rebuke/ lie' exchange, and the questions that may induce lying; 2) to identify the strategies that health-care professionals implement in order to obtain the information they seek when questioning their clients; and 3) to identify themes that refer to behavioural norms that clients might be inclined to lie about. The results are based on the assumption that there are ties between behaviour and speech acts, in this case between the transgression of behavioural norms and lying.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.752

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 studies0.0010.002
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 head0.095
GPT teacher head0.376
Teacher spread0.281 · 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