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Record W2054046813 · doi:10.1080/16066350701699031

The Sydney Laval Universities Gambling Screen: Preliminary data

2008· article· en· W2054046813 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAddiction Research & Theory · 2008
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsPsychologyGambling disorderPathologicalSample (material)EpidemiologyPsychiatryClinical psychologyMedicineAddictionPathology

Abstract

fetched live from OpenAlex

Current instruments used in epidemiological studies suffer serious methodological problems, one being the failure to properly conceptualize the constructs of problem and pathological gambling. The purpose of this study is to develop a brief single purpose survey instrument to identify prevalence rates and estimates for treatment services. The South Oaks Gambling Screen (SOGS) and Sydney Laval Universities Gambling Screen (SLUGS) were administered to a sample of 2069 college and university students in Scotland. Results showed that 4% of respondents met criteria for probable pathological gambling. SOGS scores correlated significantly with rated level of problems but less than half (44%) of those meeting SOGS criteria indicated a need for treatment. Responses on the SLUGS indicated that impaired control and spending more time and money is a feature commonly reported among non-problem gamblers. The SLUGS may represent a useful brief single purpose screen for problem gambling and self-reported need for treatment.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.339
GPT teacher head0.474
Teacher spread0.135 · 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