Bibliographic record
Abstract
Contemporary self-tracking systems signal a new era of biological monitoring now entangled with the politics of ubiquitous computing. Is self-tracking technology, which is connected to major stakeholders in healthcare, essential for filling in gaps in care, or is it fueling an increasingly commercialized medical industry? This essay examines the complex biases embedded in self-tracking technologies and introduces three manifestations of feminist science that subvert the monetization of personal health information: feminist art collective subRosa, which investigates how personal genetic information is developed into marketable medical products in their web-based project, Cell Track: Mapping the Appropriation of Life Materials; media artist and biohacker Mary Maggic, who makes self-synthesized hormone therapy accessible with their Open Source Estrogen project; artist-researcher Heather Dewey-Hagborg, whose biohacking products provide a DIY science in a world marred by genetic policing. Against the lure of connectivity, feminist science looks to circumvention as a method for understanding and disrupting the gendered and raced politics embedded in self-tracking technology. Tracing alternative techno-politics in these three new media projects, this essay reveals the necessity for artistic interventions in the contemporary healthcare landscape. Feminist art collective subRosa investigates how personal genetic information is developed into marketable medical products in their web-based project, Cell Track: Mapping the Appropriation of Life Materials. Drawing attention to the corporate ownership of biology, Cell Track adds new meaning to the idea of tracking. Similarly emphasizing the potential in citizen science, media artist and biohacker Mary Maggic makes self-synthesized hormone therapy accessible with their Open-Source Estrogen project. Both subRosa and Maggic are interested in bypassing institutional gatekeepers, not unlike artist-researcher Heather Dewey-Hagborg whose biohacking products suggest a DIY science in a world marred by genetic policing. Feminist science aims to circumvent tracking and institutional biopower against targeted populations. Against the lure of connectivity, feminist science looks to circumvention as a method for understanding and disrupting the gendered and raced politics embedded in surveillance. Working through the three bioart projects above, this essay reveals the necessity for artistic interventions in the contemporary healthcare landscape. Where commercial self-tracking products shortchange consumers by requiring them to share their health data with third-party companies, a feminist science framework and practice critically examines – and in some cases offers a departure from – the neoliberal biotechnology and medical industries.
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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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.013 | 0.067 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.017 | 0.002 |
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".