Bibliographic record
Abstract
Drawing from Michel Foucault’s discussion of the plague and smallpox epidemics, this essay unpacks the “inextricable link” between racism and biopower. By looking at the role of essential workers and ideas of differential risk in the current Covid-19 pandemic, this essay argues that Foucault’s work allows us to trace the techniques that biopower uses to generate and normalize the increased vulnerability of racialized groups. Techniques of quarantine and their exception for essential work expose the way that biopower relies on state racism through the production of differential and racialized vulnerabilities. One can draw connections between Foucault’s analysis of those of "little substance” who continued to work during plague quarantines and modern day essential workers to demonstrate how biopower protects the population by increasing and normalizing the vulnerability of an expendable subclass. Foucault explains these differentiated normalities through the smallpox epidemic, where the risk of contracting and dying of smallpox was distinguished based on age, location, profession, etc. One should build on Foucault here, and consider ‘race’ as another factor that is used to differentiate ‘normal’ levels of risk. This normalization preserves a system which makes people of colour vulnerable under the regime of biopower. While Foucault does not directly engage with race in his analysis of plagues and epidemics, his ideas on biopower provide a framework through which we can better understand the ways that racism permeates our current pandemic.
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.
How this classification was reachedexpand
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.013 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".