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Record W2800309680 · doi:10.7939/r3mw8f

Psychosocial competencies during the transition to adulthood: Trajectories and covariates

2010· article· en· W2800309680 on OpenAlexaboutno aff
Vargas Lascano

Bibliographic record

VenueUniversity of Alberta Library · 2010
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPsychologyTransition (genetics)Developmental psychologyCovariateClinical psychologySocial psychologyPsychiatryEconometricsMathematics

Abstract

fetched live from OpenAlex

This study modeled trajectories of four psychosocial competencies (autonomy, industry, identity, and intimacy) across four years of university and year-to-year covariation of these competencies with typical student experiences (living away from parents, academic performance, dating, and alcohol use) in 195 Canadian students. Analyses revealed that, on average, autonomy and identity did not change over time. Accounting for gender differences, however, revealed some linear changes across time for these competencies. Industry and intimacy showed curvilinear trajectories of change. Year-to-year, students reported higher autonomy and identity when living away from their parents and when getting higher grades. They also reported higher industry when getting higher grades. When students dated they reported higher identity and intimacy; dating women also reported higher autonomy than dating men. When dating students reported higher intimacy they reported higher perceived affection within their romantic relationships. Possible mechanisms for the observed patterns and their implications 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 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)0.004
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 score0.586
Threshold uncertainty score0.834

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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
Published2010
Admission routes1
Has abstractyes

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