We have never not been fascist: Infrastructures of state violence as technofascist laboratories
Bibliographic record
Abstract
This commentary critiques narratives of Silicon Valley exceptionalism in current efforts to diagnose technofascism. The rapid global spread of fascism has not been initiated by the current American Right, nor does the technological character of this iteration of fascism present a rupture: fascist conditions have continuously existed for peoples colonized, enslaved, indentured, exterminated, or otherwise oppressed by Western imperialism since the beginning of modernity/colonialism. Likewise, surveillance and calculative technologies-from paper to digital-have always been central in inflicting violence on these peoples because they solve issues of scale in necropolitical population control: from biometrics to track fugitive slaves, over census technologies to control and eradicate colonized peoples, to surveillance infrastructures of apartheid, to now algorithmic war machines. Now more than ever, it is urgent that we recognize that the structural conditions of this iteration of fascism have been created by modernity/coloniality and racial capitalism, and that the potential of technofascism lies in the bureaucratic-legal and calculative nature of the modern state.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.054 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".