Gambling pathways development of triad members, female sex workers, male sex workers and taxi drivers: A summary of four qualitative studies on gambling deviant subcultures in Hong Kong.
Bibliographic record
Abstract
This summary analysis was based on four ongoing qualitative studies undertaken in Hong Kong involving four active gambling subgroups----- triad-related members (n=30), female sex-workers (n=30), males sex workers (n=10), and taxi drivers (n=10). The purpose of the summary was to explore the pathways development of these subculture groups, the gambling motivations, and lifestyle. Each participant was administered the Problem Gambling Severity Index (PGSI) of the Canadian Problem Gambling Index (CPGI) (Ferris & Wayne, 2001) and the DSM-IV diagnostic criteria for Pathological Gambling (American Psychiatric Association, 2000). They were also given semi-structured clinical interviews by an experienced clinical psychologist and his students. Results indicated that the majority of the participants met the criteria for pathological gambling. Furthermore, in general, all four groups came from troubled childhoods and poor family backgrounds. Most of the participants had co-addiction problems. The lifestyle of their subculture was a significant factor for their involvement in gambling. Differences found among the groups included their motivations towards gambling? Apart from monetary gains? Their adopted gambling habits, their feelings towards gambling, and lifestyle differences. The triad-related members gambled mostly for social lingering and business purposes. Female sex workers gambled for the reward of escaping problems and bad moods. Male sex workers gambled mostly for the excitement and thrill. Taxi drivers gambled mostly for killing time. All the 4 groups of participants expressed their reluctance in seeking for treatment for their gambling problems. The summary of the four studies support the claims of the pathways development model of Blaszczynski & Nower (2002) and Hirschi? Theory on social bonding (1969).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".