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Record W7132961431

The Development of Antisocial and Prosocial Lying in Children with and without Severe Conduct Problems

2020· dissertation· W7132961431 on OpenAlexaff
Sarah Zanette

Bibliographic record

VenueTSpace · 2020
Typedissertation
Language
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsEmployment and Social Development Canada
Fundersnot available
KeywordsLyingProsocial behaviorTemptationAggressionDishonestyHelping behaviorDeceptionConduct disorder
DOInot available

Abstract

fetched live from OpenAlex

Lying is a typical part of childhood. However, for some children, such as those experiencing conduct problems, lying becomes problematic and atypical with increased age. Frequent and persistent antisocial lying is thought to be an early symptom of conduct problems. However, until the present thesis, it was unclear why children with conduct problems tell antisocial lies more than typical children. Furthermore, it was unknown whether and how often children with conduct problems tell prosocial lies (i.e., “white lies”), which are lies told to be polite or prevent hurting someone else’s feelings. This thesis outlines 3 studies (N = 316-387) examining antisocial and prosocial lie-telling among 6 to 12 year-old children with and without conduct problems. In Chapter 2, I found that while parents reported that the frequency of children’s antisocial lying increased alongside the severity of conduct problems, the frequency of their prosocial lying did not. Given that parent report methods may be unreliable due to social desirability bias or the inherent nature of lying being deceptive (i.e., parents may not catch their child lying), in Chapters 3 and 4 I examined prosocial and antisocial lying using behavioral measures. In Chapter 3, I used a disappointing gift paradigm to examine whether children would lie about liking a disappointing gift. Consistent with the parent-report results of Chapter 2, children with conduct problems were just as likely to tell a prosocial lie as typically developing children. In Chapter 4, I used a modified version of the temptation resistance paradigm to examine whether children will tell a lie to conceal a minor transgression (a form of antisocial lying). Again, consistent with the parent-report results of Chapter 2, children were more likely to tell an antisocial lie with increased conduct problems. However, theory of mind was shown to act as a protective factor against the relationship between increased antisocial lying and conduct problems. Together, my thesis suggests that children with and without conduct problems engage in different types of lying according to social context, and that socio-cognitive development may play a key role in the reduction of antisocial lying for children with conduct problems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.029
GPT teacher head0.335
Teacher spread0.307 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

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