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Record W2971567891 · doi:10.1016/j.dib.2019.104472

Dataset on childhood exposure to parenting by lying and its associations with adulthood psychosocial outcomes in a Singapore sample

2019· article· en· W2971567891 on OpenAlexaff
Peipei Setoh, Siqi Zhao, Rachel Santos, Gail D. Heyman, Kang Lee

Bibliographic record

VenueData in Brief · 2019
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsUniversity of Toronto
FundersMinistry of Education, IndiaNanyang Technological University
KeywordsLyingPsychosocialPsychologyDevelopmental psychologyYoung adultClinical psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

The present data are reported in the article "Parenting by Lying in Childhood is Associated with Negative Developmental Outcomes in Adulthood" (Setoh et al., in press). Data were collected using online survey. In this dataset, there are 377 responses from young adults from Singapore who reported on their childhood exposure to parenting by lying, their current deceptive behaviors toward parents, and their psychosocial adjustment. Path analysis was performed to better understand parenting by lying - a prevalent, but under-studied parenting practice.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.656

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 studies0.0000.000
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 head0.036
GPT teacher head0.342
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 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

Citations1
Published2019
Admission routes1
Has abstractyes

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