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Record W4240728814 · doi:10.4309//jgi.2018.38.12

Influence of Social Interaction on Women College Students’ Electronic Gambling Machine Behaviour

2018· article· en· W4240728814 on OpenAlexvenueno aff
Rory A. Pfund, Meredith K. Ginley, James Whelan, Samuel C. Peter, Briana S. Wynn, Matthew T. Suda, Andrew W. Meyers

Bibliographic record

VenueJournal of Gambling Issues · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyHumanitiesConversationSocial psychologySocial relationInterpersonal interactionAffect (linguistics)ArtCommunication

Abstract

fetched live from OpenAlex

Social influence affects college students’ gambling behaviours. However, few studies have experimentally investigated the influence of social interaction on college students’ gambling behaviour, and those studies that have yielded mixed findings. Women college students (n = 109) who endorsed recreational gambling behaviour were randomly assigned to gamble on electronic gambling machines (EGMs) in three conditions: warm social interaction from a confederate (i.e., initiating and maintaining conversation), cold social interaction from a confederate (i.e., refraining from initiating and maintaining conversation), or gambling alone. On average, participants in the warm social interaction condition placed significantly fewer spins and spent more time placing bets on the EGMs compared to the cold social interaction and no confederate conditions. When examining gambling behaviour over time, participants in the warm social interaction condition increased their bet size and the time between their bets over time compared to the cold interaction and no confederate conditions. These results suggest that interpersonal interactions significantly affect gambling behaviour. However, future research is needed to investigate these social processes in other forms of gambling and other gambling experiences.RésuméL’influence sociale affecte les comportements de jeu des étudiants collégiaux et universitaires. Cependant, peu d’études ont analysé de manière expérimentale l’influence de l’interaction sociale sur le comportement de jeu des étudiants, et les études ont donné des résultats mitigés. Les étudiantes (n = 109) qui ont adopté un comportement de jeu récréatif ont été affectées au hasard à des jeux électroniques en fonction d’une des trois conditions suivantes : avec interaction sociale amicale d’un camarade (c.-à-d., qui amorce et entretient la conversation), avec interaction sociale froide d’un camarade (qui s’abstient d’amorcer et d’entretenir la conversation) ou en solitaire. En moyenne, les participantes en condition d’interaction sociale amicale ont joué beaucoup moins de tours et ont consacré plus de temps à parier sur les appareils de jeu électroniques, comparées à ceux qui étaient en interaction sociale froide ou en solitaire. En examinant le comportement de jeu sur une période donnée, les participantes en condition d’interaction sociale amicale ont augmenté la taille des paris et la durée entre les paris par rapport à celles qui étaient dans une interaction sociale froide et en solitaire. Ces résultats font ressortir que les interactions interpersonnelles affectent de manière importante le comportement du jeu. Cependant, d’autres recherches doivent être effectuées pour analyser ces processus sociaux dans d’autres formes de jeux de hasard et d’autres expériences de jeu.

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 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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.846

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.127
GPT teacher head0.473
Teacher spread0.346 · 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 teacher head, 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

Citations1
Published2018
Admission routes1
Has abstractyes

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