Making a living online: Problem gambling and workaholism in high earning online Texas hold'em poker players
Bibliographic record
Abstract
The skill component of Texas hold'em online poker (THOP) adds a unique element to the assessment of risk for problem gambling (PG). The current study examined whether PG among a high earning subgroup of THOP players was analogous to workaholism. Participants were self-selected online poker players (N = 31), and results revealed that participants played an average of 30.5 hours per week, and had an average annual online poker earning of CAD 29 995. Furthermore, 32% of the sample gambled problematically according to the PGSI. In accordance with previous findings, PG was uniquely predicted by time played and stress. However, PG in this subset of THOP players was associated with an external locus of control. Contrary to expectations, the personality variable of neuroticism was unrelated to PG and workaholism. Furthermore, workaholism was unrelated to any variables in the model, and no significant relationship emerged between workaholism and PG.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".