Gambling as activity: Subcultural life-worlds, personal intrigues and persistent involvements <xref ref-type="note" rid="fn1"><sup>1</sup></xref>
Bibliographic record
Abstract
Although gambling is often envisioned as a disreputable if not also a personally and socially destructive realm of endeavor, this paper approaches gambling as a realm of activity in a more generic, pluralist sense. Employing Henry Lesieur's (1977) portrayal of gambling in The Chase as an ethnographic focal point, this paper not only attempts to "permeate the deviant mystique" that surrounds gambling, but also endeavors to provide a set of conceptual, methodological and textual resources that could inform the study of gambling or other involvements of a parallel sort. Thus, while appreciating the relevance of Henry Lesieur's The Chase for the study of gambling more specifically, this statement also draws attention to the contributions (envisioning Henry Lesieur's text as a prototype) that more sustained and detailed ethnographic studies of gambling as activity can make to the broader social science enterprise. In a related way, whereas more intense gambling often is explained as an individual quality (or affliction), this statement examines gambling more centrally as a subcultural process. Thus, gambling is approached as situated, career, fascinated, and persistent instances of activity that can be adequately understood only within a socially constituted life-world.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.036 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.001 | 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".