Feminist Surveillance Studies and the Institutionalization of Interphobia
Bibliographic record
Abstract
Though sex, gender, and sexuality have been subject to ongoing forms of state scrutiny and, therefore, concern surveillance studies scholars—one can think of McCarthy and the policing of homosexuality and the current forms of homophobia and cisgenderism structuring bathroom, sport, and “Don’t Say Gay” laws in the US—there is a glaring lack of attention paid to the violent (colonial) state, legal, and medical projects that surveil intersex people’s body-minds with the (eugenic) goal of eradicating intersex variations to make sex, gender, and sexuality “legible,” dyadic. There is a lack of attention paid to intersex issues in mainstream media as well as from surveillance studies scholars. As a result, as scholars reflect backward over the decades of scholarship in surveillance studies in this anniversary issue of Surveillance & Society, we posit that it is time to use the refined tools surveillance studies offers in service of opposing the often-ignored ongoing surveillance—and killing project—of intersex people’s unique sex traits. In doing so, we focus our attention on surgical interventions, medical photography, and the reproductive technology preimplantation genetic diagnosis. These three case studies offer a sampling of the various ways intersex variations are surveilled and eradicated, and, therefore, signal the importance of integrating intersex issues into feminist surveillance studies. To conclude, we address how intersex activists find each other and propel their activism—activism that combats the surveiling and regulating nature of state and medical-sanctioned interphobia—into the mainstream via information and communication technologies. And yet, there remains so much work to be done. We end on the cautionary note that the ways that intersex activists’ work is routinely stymied and undermined by state and medical forces must be considered.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.073 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".