Why Swedish people play online poker and factors that can increase or decrease trust in poker Web sites: A qualitative investigation
Bibliographic record
Abstract
Three face-to-face focus groups that included 24 online poker players were conducted in Stockholm to investigate their motivations for playing online poker and issues relating to their trust of poker Web sites. Casual players played because they liked the convenience, the ease of learning, the low stake size, the relief from boredom, and the social interactions. "Professional" players played to win money and utilised several features of the online game for psychological tactics. They also tended to play several tables at once. Factors that affected how much a player would trust an online poker Web site included the size and reputation of the operator, the speed with which winnings were paid out, the clarity of the Web site design, the technical reliability of the service, and the accessibility and effectiveness of the customer service. Responsible gaming measures also increased levels of trust by demonstrating company integrity and by reducing anxiety about winning from other players. The findings indicate that providing a safe online environment with effective responsible gaming measures may be much more than just a moral and regulatory requirement. Players in this study suggested that such features are sometimes necessary in order to achieve an enjoyable gaming experience. Consequently, responsible gaming initiatives and good business practice do not have to be mutually exclusive. Indeed, in this particular scenario, they might even be considered mutually dependent. This project was funded by Svenska Spel, the operators of the Swedish National Lottery. Other than agreeing to the research question, Svenska Spel had no say in how the research was carried out, the results that were reported, the conclusions that were drawn, or the editing of the report.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".