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Record W2104585629 · doi:10.1177/0165025414542712

Self-regulation among youth in four Western cultures

2014· article· en· W2104585629 on OpenAlexaffabout
Steinunn Gestsdóttir, G. John Geldhof, Tomáš Paus, Alexandra M. Freund, Sigrún Aðalbjarnardóttir, Jacqueline V. Lerner, Richard M. Lerner

Bibliographic record

VenueInternational Journal of Behavioral Development · 2014
Typearticle
Languageen
FieldPsychology
TopicBehavioral Health and Interventions
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPsychologyConfirmatory factor analysisMeasurement invarianceGermanDevelopmental psychologyIcelandicSocial psychologyCross-cultural studiesPositive Youth DevelopmentMeaning (existential)Structural equation modelingStatistics

Abstract

fetched live from OpenAlex

We address how to conceptualize and measure intentional self-regulation (ISR) among adolescents from four cultures by assessing whether ISR (conceptualized by the SOC model of Selection, Optimization, and Compensation) is represented by three factors (as with adult samples) or as one “adolescence-specific” factor. A total of 4,057 14- and 18-year-old youth in Canada, Germany, Iceland, and the US participated. Confirmatory factor analyses did not confirm a tripartite model of SOC in any sample, whereas a single (nine-item) composite fit in all samples. A partial weak factorial invariance model showed a roughly equivalent meaning of the nine-item composite among German, Icelandic, and US youth. We discuss the need for further examination of the relative importance of items among Canadian youth, and possible problems using reverse-coded items with adolescents. The similarities that were observed across age and cultural groups suggest that a single factor structure of SOC, as measured by nine items, may be robust for youth in Western cultural settings and that SOC processes are not fully developed until adulthood.

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)0.001
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 score0.098
Threshold uncertainty score0.195

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.063
GPT teacher head0.399
Teacher spread0.336 · 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

Citations29
Published2014
Admission routes2
Has abstractyes

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