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Record W7024652207

The Situational Analysis of Problem Gamblers in Recovery: An Action Research Study

2021· other· en· W7024652207 on OpenAlexaboutno aff

Bibliographic record

VenueNSUWorks (Nova Southeastern University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSituational ethicsQualitative researchExploratory researchAction (physics)Focus groupStigma (botany)Thematic analysisNarrativeAction research
DOInot available

Abstract

fetched live from OpenAlex

As of 2012, there were more than 100 studies on the prevalence and social impact of problem gambling in Canada. However, few qualitative psychological studies specifically explored the process of therapy for problem gamblers. This research initiative attempts to bridge this notable gap in the literature. In this action research inquiry, I explore the recalled experiences of therapeutic interactions of six problem gamblers and six registered clinical counsellors. The participants engaged in focus groups, individual interviews, and a teleconference that helped to foster a greater understanding of the stigma attached to “being” a problem gambler. Although there are many comprehensive works on the topic of stigma, I felt the quintessential work of Erving Goffman (1963) on the moral management of stigma and spoiled identity was a fitting lens through which to examine the plight of the problem gambler in counselling. In this exploratory inquiry, I found many examples of participant gamblers morally managing their identities, agentively adopting, challenging, or resisting various descriptions of their stigmatized status. My situational analyses highlighted how clients engaged in “healthy” resistance, agentively managing the potential for stigmatized or spoiled identities. These shared narratives brought awareness to the marginalized status of “being” a problem gambler, while providing an appreciation of ways in which clients and counsellors can collaboratively promote preferred ways of being. These findings also indicate that further sensitivity may be required for practitioners providing services to stigmatized populations, such as the individual with gambling problems. Implications for counselling theory, practice, and possible future research are discussed.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.573
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0100.016
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.145
GPT teacher head0.365
Teacher spread0.220 · 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.

Study designObservational
Domainnot available
GenreOther

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

Citations0
Published2021
Admission routes1
Has abstractyes

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