Bibliographic record
Abstract
The digitization of health by biotech firms is sedimenting flows of data for authoritarian rule. In this short commentary I argue for a dialectic approach to understanding how technofascist authoritarianism is being naturalized in the name of combatting disease: I think relationally between the “internal” logics that generate racialized and vulnerable threats, while taking seriously the “external” sociopolitical conditions that make such generations possible. I start from three different sites. First, the map, through which the biotech firm BlueDot Orientalizes disease and sells AI (artificial intelligence)-generated forecasts to cities, airlines, and military alliances. Second, the maternity ward, where Palantir—which has refined its AI systems through Israel's war on Gaza—is collecting patient information to feed new generative AI. And third, the mosquito, whose reproduction Verily (of Alphabet) is arresting via AI to prevent malaria. Drawing lines across these topographies of violence reveals both contradictions and sites for resistance.
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 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 | 0.020 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.058 |
| Scholarly communication | 0.019 | 0.019 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.012 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".