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Record W2549474714 · doi:10.1177/0091415016677973

Older Adults’ Casino Gambling Behavior and Their Attitudes Toward New Casino Development

2016· article· en· W2549474714 on OpenAlexaff
Anthony Piscitelli, J. Hartwell Harrison, Sean Doherty, Barbara A. Carmichael

Bibliographic record

VenueThe International Journal of Aging and Human Development · 2016
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsPsychologyAdvertisingSocial psychologyBusiness

Abstract

fetched live from OpenAlex

Research on new casinos typically focuses upon their impact on the community, rather than on specific at-risk groups. This research study explores the impact of the opening of a new casino on attitudes of older adult casino patrons, especially those at particular risk of having gambling problems. Results demonstrate that over 80% of older adult casino patrons would not change their attitudes toward gambling or expect to increase their gambling as a result of the opening of a new casino. However, older adults with problem gambling issues are more likely to indicate they would visit a casino more, spend more time at a casino, and gamble more as a result of the opening of a new casino. In addition, older adults with signs of a gambling problem are more likely to say the opening of a new casino would change their opinions of gambling in general or casino gambling.

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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.104
GPT teacher head0.379
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

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

Citations5
Published2016
Admission routes1
Has abstractyes

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