Bibliographic record
Abstract
Abstract This book argues that we live in an age of somatic subjects, whose authentic identity must be represented through the body. When a perceived mismatch between inner self and outer form occurs, technologies can step in to change the flesh. Drawing on Wittgenstein's objections to the idea of a private language, and on Foucault's critical account of normalization, this book shows how we have been led to think of ourselves in this way, and suggests that breaking the hold of this picture of the self will be central to our freedom. How should we work on ourselves when so often the kind of self we are urged to be is itself a product of normalization? This question is answered through three case studies that analyze feminist interpretations of transgender politics, the allure of weight-loss dieting, and representations of cosmetic surgery patients. Mixing philosophical argument with personal narrative and analysis of popular culture, the book moves from engagement with Leslie Feinberg on trans liberation, to an auto-ethnography of Weight Watchers meetings, to a reading of Extreme Makeover, to the author's own practice of yoga. The book draws on philosophy, sociology, medicine, cultural studies, and psychology to suggest that these examples, in different ways, are connected to the picture of the somatic subject. Working on the self can both generate new skills and make us more docile; enhance our pleasures and narrow our possibilities; encourage us to take care of ourselves while increasing our dependence on experts. Self transformation through the body can limit us and liberate us at the same time. To move beyond this paradox, the book concludes by arguing that Foucault's last work on ethics provides untapped resources for understanding how we might use our embodied agency to change ourselves for the better.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.025 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.018 | 0.004 |
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".