Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The spread of Internet gambling has raised several issues concerning motivations to gamble, consumer behaviour online, problem gambling, security of Web sites, and fairness and integrity of the games. Rather surprisingly, however, there has been little in the way of research regarding online crime and Internet gambling even though it is an urgent priority. This article addresses this absence by investigating the types, techniques, and organizational dynamics of online crime at the portals of Internet gambling sites. Our approach is qualitative in nature and explores, using document analysis, the activities of cybernomads, dot.con teams, and criminal networks. We demonstrate that there are different levels of criminal organization, distinguished by their complexity of division of labour; coordination of roles; purposefulness of association between criminals; and ability to avoid, evade, or neutralize security systems and law enforcement. We conclude by arguing that conventional understandings of real-world gambling-related criminal relationships have been altered by the digital environment of the Internet.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it