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Record W2078104137 · doi:10.1007/s10683-012-9324-x

Why do people tell the truth? Experimental evidence for pure lie aversion

2012· article· en· W2078104137 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

VenueExperimental Economics · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicExperimental Behavioral Economics Studies
Canadian institutionsVanier CollegeUniversité du Québec à Montréal
Fundersnot available
KeywordsPsychologyContext (archaeology)Relevance (law)Social psychologyPositive economicsEpistemologyEconomicsPhilosophyLawPolitical science

Abstract

fetched live from OpenAlex

Abstract A recent experimental literature shows that truth-telling is not always motivated by pecuniary motives, and several alternative motivations have been proposed. However, their relative importance in any given context is still not totally clear. This paper investigates the relevance of pure lie aversion, that is, a dislike for lies independent of their consequences. We propose a very simple design where other motives considered in the literature predict zero truth-telling, whereas pure lie aversion predicts a non-zero rate. Thus we interpret the finding that more than a third of the subjects tell the truth as evidence for pure lie aversion. Our design also prevents confounds with another motivation (a desire to act as others expect us to act) not frequently considered but consistent with much existing evidence. We also observe that subjects who tell the truth are more likely to believe that others will tell the truth as well.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.088
GPT teacher head0.369
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