Bibliographic record
Abstract
Thus far, little attention has been paid by Foucauldian scholars to the role of laughter in our subjectivation and normalization, nor to the possible roles of laughter practices in political resistance. Yet, there is a body of references to laughter in both Foucault’s own work and that of his contemporary commentators, subtly indicating that it might be a tool for challenging normalization through transgression. I seek to negotiate the different functions (both transgressive and disciplinary) that our laughter practices can have, proposing that laughter is a worthy site of exploration for Foucauldian feminists in particular. Examining the differential norms, requirements, and sanctions around laughter shows that we are shaped as gendered subjects through the regulation of laughter’s timing and its bodily presentation. I argue that the contemporary state of laughter practices works to uphold docile femininity, using tools such as compulsory happiness and labelling feminists as killjoys. In brief, this article interrogates the ways in which cultivating different laughter practices can function as a path for Foucauldian-feminist political resistance.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.148 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".