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Record W1942714605 · doi:10.4309/jgi.2004.11.13

Loneliness and life dissatisfaction in gamblers

2004· article· en· W1942714605 on OpenAlexvenueno aff
James N. Porter, Julia Ungar, G. Ron Frisch, Reena Chopra

Bibliographic record

VenueJournal of Gambling Issues · 2004
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsLonelinessPsychologyRecreationUCLA Loneliness ScaleScale (ratio)Clinical psychologySocial psychology

Abstract

fetched live from OpenAlex

This exploratory study examines the manifestation of two experiential variables in undergraduate university students who gamble. The study had 829 participants (270 males and 559 females). They completed self-report questionnaires on gambling-related problems (the South Oaks Gambling Screen), loneliness (the Social and Emotional Loneliness Scale for Adults), and overall life satisfaction (the Satisfaction with Life Scale). Based on their scores on the South Oaks Gambling Screen, participants were divided into two groups: recreational gamblers and at-risk gamblers. Male participants were much more likely to be at-risk gamblers than female participants. Compared to female recreational gamblers, female at-risk gamblers were found to be less satisfied with their lives and lonelier, especially in the romantic and social realms. Male recreational and at-risk gamblers did not differ significantly on these factors. Results support the views that the internal experience of female at-risk gamblers differs from that of their male counterparts, and that loneliness is best considered as a multidimensional construct.

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)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.241
GPT teacher head0.456
Teacher spread0.215 · 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

Citations24
Published2004
Admission routes1
Has abstractyes

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