Health Theatre: Recognizing and subverting the tactical farce of the medicalization of everyday life
Bibliographic record
Abstract
This article considers the implications of Western health and wellness culture’s strategic co-option by industry, embodied by the rise of wearable tech, the commodification of the self-help movement, and the datafication of the human body. Said culture has come to bear the paranoia observable in the West’s approach to national security, which is widely dubbed as “security theatre”. “Health theatre” is put forth here as an analogous phenomenon to security theatre, wherein the populous is subject to invasive scrutiny by governing structures, enacted in the name of their own wellbeing. Both phenomena are characterized by their sensationalist rhetoric and effective impotence in producing results consistent with their alleged purpose. Health theatre can best be understood as an organic symptom of the broad medicalization that has permeated Western culture over the past century. Medicalization pathologizes the scope of human experiences, while situating the problem at the level of the individual where solutions are then couched. Further, by positing health as an elusive state to be perennially pursued, the individual is left in a perpetual state of dependency. Should health theatre proliferate, the West will continue to suffer a fear-based, atomizing system of health promotion. Means of resistance to health theatre are proposed here as a return to engagement with communal forms of reproductive care that reject pathologizing diversity in psychological and somatic states.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.055 |
| Scholarly communication | 0.013 | 0.011 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".