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Record W2802995963 · doi:10.4309/jgi.2018.38.3

A new look at the coping strategies used by the partners of pathological gamblers

2018· article· en· W2802995963 on OpenAlexaffvenue
Mélissa Côté, Joël Tremblay, Natacha Brunelle

Bibliographic record

VenueJournal of Gambling Issues · 2018
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsPsychologyViewpointsHumanitiesSocial psychologyContext (archaeology)SociologyArt

Abstract

fetched live from OpenAlex

People living with pathological gamblers (PGs) have to endure the negative consequences of their problem gambling. It is known that the partners of PGs will develop adaptation strategies to cope with gambling behaviour. However, research conducted on the topic is still in its early stages. The goal of this study was to draw up a portrait of the strategies employed, their context, means, and main goals, and to examine the variation of these strategies over time and the viewpoints of the 2 members of the couple. Using 19 semi-structured interviews, we noted that the partners used some 30 strategies aiming primarily at modifying the gamblers’ pathological behaviour, and also at improving their own personal well-being. An analysis of the usage context illustrated the many possible interactions which occurred between individuals and their environment and which triggered a strategy’s use. Generally speaking, both members of the couple had a similar perception of the strategies used by the partners. When partners realized that they had not influenced the PGs’ habits, they sometimes changed adaptation strategies.RésuméLes partenaires de joueurs pathologiques (JP) vivent des conséquences négatives découlant des habitudes problématiques de jeux de hasard et d’argent (JHA) de leur conjoint.. Il est reconnu que les partenaires de JP mettront en place des stratégies d’adaptation pour faire face à ces comportements de JHA. Toutefois, les recherches effectuées sur le sujet en sont encore à leurs premiers balbutiements. L’objectif de cette étude vise à dresser un portrait des stratégies utilisées, leurs contextes d'utilisation, les moyens et les finalités recherchées, en plus de s’intéresser au point de vue des deux membres du couple et à la variation dans le temps de ces stratégies. À l'aide de dix-neuf entrevues semi-structurées, on remarque que les partenaires ont utilisé près d'une trentaine de stratégies visant principalement une modification des comportements de JHA du JP, mais aussi l'amélioration de leur bien-être personnel. L'analyse des contextes d’utilisation illustre les nombreuses interactions possibles entre l'individu et son environnement qui déclenchent l’utilisation d’une stratégie. De façon générale, les deux membres du couple ont une perception similaire des stratégies utilisées par l’autre partenaire. Enfin, lorsque les partenaires prennent conscience qu'elles n'ont pas influencé les habitudes de JHA du JP, elles changent parfois de stratégies d’adaptation.

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)0.003
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.327
GPT teacher head0.489
Teacher spread0.162 · 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 designQualitative
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

Citations12
Published2018
Admission routes2
Has abstractyes

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