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Record W4403927112 · doi:10.5539/res.v16n2p1

ICT, Leisure Time, and Personality Traits of Members of Generation Z: Those Who Spend More Time With Friends Feel Happier

2024· article· en· W4403927112 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueReview of European Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicGenerational Differences and Trends
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyBig Five personality traitsPersonalitySocial psychologyLeisure timeInformation and Communications TechnologyDevelopmental psychologyWorld Wide WebPhysical activityComputer science

Abstract

fetched live from OpenAlex

This study examined how adolescents and young adults perceive themselves, their personal characteristics, leisure habits, media usage habits, vitality, activity, belonging, happiness, self-esteem, determination, initiative and motivation, and belonging to a global and local community. Data from 537 adolescents and young adults aged 13-24 were collected in Israel in 2022. The findings revealed a connection between spending leisure time with friends and happiness. Two different clusters emerged from the study. The participants associated with cluster 1 were characterized by higher averages on all scales; a higher percentage of participants aged 18+ was found in cluster 1; participants in cluster 1 spent more hours with friends than did participants in cluster 2.

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.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.495
Threshold uncertainty score0.302

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.091
GPT teacher head0.366
Teacher spread0.275 · 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