Bibliographic record
Abstract
The purpose of this paper is to explore the work/leisure binary as it relates to labeling, stereotyping and ultimately stigmatizing persons with disabilities. Although less deliberated in the literature, stigma depends on social context, a class or category of undesirable behaviors practiced by the actor, in the present case—leisure. The evolution of leisure as a stigmatized class of human activity is addressed, with special attention to the intersection of work and disability and how inability to work has come to stigmatize the leisure of persons with disabilities. Usual and customary stigma management strategies employed by abled citizens are reviewed. For the child, the currently employed and even the retired, seriousness or employment, or both justify and legitimize their use of leisure. No such alternatives are available to the unemployed majority of persons with disabilities. Finally, the implications of inclusive leisure are explored, how it confronts stigma and may be used as a basis for changing the general perception of leisure by a lay audience. Inclusive leisure is an expression of equal rights; it confronts the stigma of leisure in two ways. First, by comingling with the abled, the demarcation between normal and abnormal dissolves into diversity and appreciation of differences. Second, inclusive leisure challenges the validity of a work/leisure binary. Because it contains the cosmetic appearances of work-- earnestness, a career-like calling, and utility-- serious leisure is suggested as a method of transition from inclusion to the recognition that leisure is a valuable activity.
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.
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 | 0.008 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.025 | 0.058 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.005 | 0.008 |
| 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".