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Record W2082521037 · doi:10.4309/jgi.2005.14.10

"Double trouble": The lived experience of problem and pathological gambling in later life

2005· article· en· W2082521037 on OpenAlexaffvenue
Gary Nixon, Jason Solowoniuk, Brad Hagen, Robert J. Williams

Bibliographic record

VenueJournal of Gambling Issues · 2005
Typearticle
Languageen
FieldPsychology
TopicGambling Behavior and Treatments
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsPathologicalPsychologyNarrativePhenomenology (philosophy)Older peopleLived experienceHermeneutic phenomenologyQualitative researchDevelopmental psychologySocial psychologyClinical psychologyGerontologyPsychotherapistMedicineSociology

Abstract

fetched live from OpenAlex

Objective: The objective of this phenomenological qualitative study was to explore the lived experience of older adults who engage in problem or pathological gambling. Method and sample: Older adults who gambled were recruited and were administered two gambling screens to ensure that they met the criteria for problem or pathological gambling. Eleven problem-pathological gamblers were identified and contributed their narratives via in-depth interviews about their experiences of problem or pathological gambling. Results: Several themes arising from the interviews were similar to patterns identified with younger gamblers, yet distinct patterns emerged. Some older gamblers gamble as an opportunity to break away and escape from traditional roles and go to extreme measures to continue their gambling while hiding it from significant others. Conclusion: Despite research suggesting few seniors encounter problems with gambling, this qualitative study suggests that gambling can have devastating consequences. Older adults may have lessened ability and time to recover from these consequences or from hitting bottom. Key words: gambling, narrative, older adults, problem-pathological gambling, phenomenology, aged

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)0.007
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 score0.004
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.007
Scholarly communication0.0030.004
Open science0.0010.006
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.000

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 head0.347
GPT teacher head0.461
Teacher spread0.114 · 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

Citations27
Published2005
Admission routes2
Has abstractyes

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