Digital Epidermalization: Race, Identity and Biometrics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article considers the ways in which what Paul Gilroy terms ‘epidermal thinking’ operates in the discourses surrounding certain surveillance practices and their applications, with a focus on identification documents and biometric technologies in particular. My aim is not to re-ontologize race, but instead to outline the notion of digital epidermalization, stemming from Frantz Fanon’s concept of epidermalization, as it allows for thinking through race, ontological insecurity and the ways in which the body materializes with and against biometric technologies. I examine key research in surveillance studies, governmental policy documents concerning biometric enabled identification documents and the 2003 ‘deportation’ to India of a Canadian citizen through the issuance of an expedited removal order by the US Immigration and Naturalization Services. By interrogating how digital epidermalization gains meaning and is put into practice, this article seeks to posit a space for refusals of such epidermal thinking through a critical biometric consciousness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it