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Record W1977733758 · doi:10.4309/jgi.2012.27.11

The Effect of Mere Presence on Electronic Gaming Machine Gambling

2012· article· en· W1977733758 on OpenAlexvenueno aff
Matthew Rockloff, Nancy Greer, Lionel G. Evans

Bibliographic record

VenueJournal of Gambling Issues · 2012
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCrowdsPsychologyAffect (linguistics)WitnessLaptopSocial psychologyAdvertisingCommunicationComputer scienceComputer securityBusiness

Abstract

fetched live from OpenAlex

Intensification of gambling behavior may partly result from arousal caused by the mere physical presence of others in the gaming venue moving through the gaming floor on their way to enjoy other amenities. In an experiment, 56 male and 76 female participants (N=132) gambled on a laptop-simulated electronic gaming machine (EGM), either alone or with a simulated crowd of 6 or 26 others who were wearing blindfolds and earphones. These crowds of other persons were falsely said to be participating in another experiment on sensory deprivation. Among players with preexisting gambling problems, the results showed that these crowds contributed to a particular style of gambling whereby players generally bet smaller amounts but were more persistent as losses mounted. These changes in persistence occurred despite the inability of these others to witness or evaluate the participants. The experiment suggests that the mere presence of others in a gaming venue can affect EGM betting behavior.

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)0.006
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 score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.123
GPT teacher head0.453
Teacher spread0.330 · 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

Citations7
Published2012
Admission routes1
Has abstractyes

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