Counter-collaborations towards alternative bio-securitizations
Bibliographic record
Abstract
In this commentary, we argue that geographical thought and praxis must engage with repressive biosecurity and biosurveillance systems and fight for alternatives. In doing so, geographers can contribute to an emerging anti-colonial and anti-racist interdisciplinary science. We suggest two counter-collaborations towards alternative bio-securitizations: working with those who have been cast out of biopolitical worlds and have long been fostering life for their communities; and working with practitioners of hegemonic science to re-direct biomedical efforts. Building these collaborations would orient biosecurity praxis to those biosecuritizations that already exist at the margins of violent security programs and foster communal and just care relations as the foundation for a liberatory and interdisciplinary science.
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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 | 0.032 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.061 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.004 | 0.021 |
| Research integrity | 0.022 | 0.027 |
| 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".