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Record W2734372955 · doi:10.1111/desc.12585

Telling young children they have a reputation for being smart promotes cheating

2017· article· en· W2734372955 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

VenueDevelopmental Science · 2017
Typearticle
Languageen
FieldNeuroscience
TopicPsychology of Moral and Emotional Judgment
Canadian institutionsChild and Family Research InstituteUniversity of Toronto
Fundersnot available
KeywordsTemptationReputationCheatingPsychologyControl (management)Social psychologyTask (project management)Affect (linguistics)Developmental psychologyInternet privacyEconomicsComputer scienceCommunicationPolitical science

Abstract

fetched live from OpenAlex

The present research examined the consequences of telling young children they have a reputation for being smart. Of interest was how this would affect their willingness to resist the temptation to cheat for personal gain as assessed by a temptation resistance task, in which children promised not to cheat in the game. Two studies with 3- and 5-year-old children (total N = 323) assessed this possibility. In Study 1, participants were assigned to one of three conditions: a smart reputation condition in which they were told they have a reputation for being smart, an irrelevant reputation control condition, or a no reputation control condition. Children in the smart reputation condition were significantly more likely to cheat than their counterparts in either control condition. Study 2 confirmed that reputational concerns are indeed a fundamental part of our smart reputation effect. These results suggest that children as young as 3 years of age are able to use reputational cues to guide their behavior, and that telling young children they have a positive reputation for being smart can have negative consequences.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
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 head0.092
GPT teacher head0.314
Teacher spread0.222 · 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