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Record W2031489186 · doi:10.1080/14459795.2013.819934

A big hole with the wind blowing through it: Aboriginal women's experiences of trauma and problem gambling

2013· article· en· W2031489186 on OpenAlexaffabout
Brad Hagen, Ruth Grant Kalishuk, Cheryl L. Currie, Jason Solowoniuk, Gary Nixon

Bibliographic record

VenueInternational Gambling Studies · 2013
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPsychologyMoodSocial issuesSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

Although studies have shown a link between social trauma and problem gambling (PG), there is little research involving Aboriginal women in this area, despite Aboriginal women being potentially at higher risk for both social trauma and problem gambling. This article describes the results of a qualitative phenomenology study asking seven Aboriginal women living in Western Canada to describe their experiences of social trauma and gambling problems. Results suggest four main themes, describing: (1) the Aboriginal women's experiences of social trauma (‘the three tigers’); (2) their use of gambling to cope with these experiences (‘a big hole with the wind blowing through it’); (3) their experience of problem gambling (‘I'm somebody today’); and (4) their process of healing from social trauma and gambling problems (‘a letter to John’). Participants described what they felt was a clear link between social trauma and problems with gambling, and how gambling helped to change their mood and block out the past. The results raise the possibility that Aboriginal women with gambling problems may need support to heal from social trauma – including racism and colonization – and that upstream initiatives to reduce the incidence of social traumas may be an important response to problem gambling among Aboriginal women.

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)0.000
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.537

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.099
GPT teacher head0.422
Teacher spread0.322 · 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 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

Citations16
Published2013
Admission routes2
Has abstractyes

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