Rethinking leisure and self : Three theorists for understanding computer and video game leisures
Bibliographic record
Abstract
Computer and video games present a powerful challenge to assumptions held in leisure literature about the value and quality of leisures. Although typically viewed as negative, computer-based leisures are one of the fastest growing segments in terms of participation and revenue-generation. Where disciplines like game studies and cultural studies have embraced the possibilities for self-development in computer and video gaming, leisure studies has (with few exceptions) either ignored the role that virtual leisures play, or reduced virtual leisures to perversions of existing leisure activities. In this article we consider how computer and video games – virtual leisures – must be understood in their own terms without being reduced to traditional assumptions about leisures. A primary misunderstanding about virtual leisures is an implicit but flawed opposition of the ‘real’ and the ‘virtual’, where physicalism is set as the gold standard for leisures. We consider how three thinkers – John Cage, Henri Lefebvre, and Gaston Bachelard – create a new language for understanding how virtual leisures are expressions of space and place that engage human beings on physiological, emotional, and mental levels. We consider how computer and video gaming throw conventional assumptions about leisures into relief, and introduce new questions about embodiment and expression. Given research demonstrating beneficial outcomes of virtual leisures, we suggest revisiting the negative judgments about virtual leisures and call for understanding the fascination with these manifestations of leisures.
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How this classification was reachedexpand
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 | 0.002 | 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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".