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Record W3133957880 · doi:10.1111/sode.12518

Time alone well spent? A person‐centered analysis of adolescents' solitary activities

2021· article· en· W3133957880 on OpenAlexafffund
Will E. Hipson, Robert J. Coplan, Morgan Dufour, Katherine R. Wood, Julie C. Bowker

Bibliographic record

VenueSocial Development · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychological and Temporal Perspectives Research
Canadian institutionsCarleton University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsSolitudeLonelinessPsychologyDevelopmental psychologyConstructiveAffect (linguistics)Social psychologyPsychotherapist

Abstract

fetched live from OpenAlex

Abstract Although solitude has been portrayed as a potentially constructive domain in adolescence, time alone has been consistently associated with socio‐emotional maladjustment. To address this discrepancy, we explored how adolescents spend their time alone and the links between solitary activities and adjustment outcomes. Adolescents ( N = 869, 68% female, M age = 16.14 ± .50) completed self‐report measures assessing time alone, solitary activities, and indices of adjustment. Latent class analysis revealed three distinct groups based on solitary activities: Passive Media (53.3%), Engaged (i.e., constructive activities; 31.7%), and Thinking (15%). Differences also emerged among these three groups in terms of time alone, negative affect, and loneliness. Implications for the role of solitude in adolescent well‐being 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)0.002
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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.075
GPT teacher head0.357
Teacher spread0.282 · 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

Citations48
Published2021
Admission routes2
Has abstractyes

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