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Record W2113516660 · doi:10.1177/0022022114535485

Development of Cultural Perspectives on Verbal Deception in Competitive Contexts

2014· article· en· W2113516660 on OpenAlexaffabout
Dana Dmytro, Jesse Ho-Yin Lo, Jennifer O’Leary, Genyue Fu, Kang Lee, Catherine Ann Cameron

Bibliographic record

VenueJournal of Cross-Cultural Psychology · 2014
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of TorontoUniversity of British Columbia
Fundersnot available
KeywordsDeceptionLyingHarmStatement (logic)PsychologySocial psychologyCultural diversityNonverbal communicationDevelopmental psychologyEpistemologyLawPolitical science

Abstract

fetched live from OpenAlex

Verbal deception may be considered morally reprehensible or acceptable depending on culturally relevant contextual factors and ethical perspectives. In the current study, Euro-Canadian ( n = 180) and Han Chinese ( n = 180) children ages 8 to 16 were recruited to investigate their moral evaluations of lying and truth-telling in competitive situations. The participants classified a story character’s statement told to either harm or help themselves or collectives of various group sizes (i.e., their class, school, or country) as a lie, the truth, or something else. Participants then made moral judgments regarding the statements and provided justifications for their evaluations. Chinese children’s evaluations became more nuanced with age: They evaluated lies told to benefit a collective as less negative than Canadian children, and truths told to harm a collective as more negative. These evaluations became more pronounced with the increasing size of the collectivity. Cultural and contextual factors relevant to evaluations and justifications of verbal deception are discussed.

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.

How this classification was reachedexpand

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.842
Threshold uncertainty score0.872

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.089
GPT teacher head0.473
Teacher spread0.384 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2014
Admission routes2
Has abstractyes

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