Evolving Understandings of Bingo in Four Decades of Literature: From Eyes Down to New Vistas
Bibliographic record
Abstract
Bingo is a distinct, enduring but understudied form of gambling. It provides comfort and pleasure to many of its players while also causing harm to some. While traditionally seen as low harm, it is being reshaped by technological and regulatory change. Despite this, there is no recent overview of the literature on bingo. This narrative review seeks to fill this gap by exploring the development of literature on bingo since the 1980s, first providing a chronological overview of writing on bingo and then a brief account of major themes in the literature. The literature reviewed was primarily identified through searches of academic databases using search terms such as betting, bingo, electronic and gambling. We find that bingo research makes a number of important contributions: it allows better understanding of groups of overlooked gamblers, corrects biases in gambling literature, highlights the importance of social and structural factors in understanding gambling and employs methodological approaches that are congruent with the people and practices being studied. Additionally, it provides new perspectives on gambling in terms of skill, affect, harm and control and offers a distinct viewpoint to analyse gambling and other phenomena.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.009 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".