Surveillance, Capitalism, Leisure, and Data: Being Watched, Giving, Becoming
Bibliographic record
Abstract
This conceptual paper aims to serve two purposes: 1) introduce theories of surveillance to aid leisure scholars in exploring surveillance in its many forms; and, 2) add to the discussion on surveillance by layering “the leisure body” onto existing theory. We begin by introducing three groupings of “surveillance” theory: panoptic surveillance (think Bentham and Foucault), post-panoptical surveillance (think Deleuze), and contemporary surveillance (Galič et al., Citation2017). Panoptic surveillance is a physical surveillance (reliant on a fleshy body and physical space) where, like in Bentham’s and Foucault’s panopticons, the individual polices personal presentation and action under the presumption of being watched. We theorize this as surveillance on the body; it is body-to-body even as it is mediated through technology. Post-panoptical surveillance is less dependent on distinct, physical spaces, and particularly those of enclosure. We theorize this as the digital merging with the physical, where surveillance comes from the interaction of the technological with the fleshy body. Although this surveillance is less reliant on specific times and spaces—occurring within or through the body—it is nonetheless conditioned by our physical connections to technological devices. This is technology-to-body surveillance that is dependent on a physical interaction between the two. Contemporary surveillance is not dependent upon a physical linkage between technology and the body or a space of enclosure; it both marks an individual and simultaneously dissolves them into an ocean of big data. It is an inescapable surveillance as existence in the modern world. We call this technobody surveillance where the need for the interaction between technologies and fleshy bodies is subsumed by the gaseous and pervasive nature of apparatuses of surveillance. With each, we provide an exemplar from leisure practice, time, and/or space to illustrate how each operates within leisure phenomena.
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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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".