Promises of Cyborgs: Feminist Practices of Posthumanities (Against the Nested Crises of the Anthropocene)
Bibliographic record
Abstract
The cultural technologies of gender, race and empire drive much of the present Anthropocene crisis, now and in the past.Everyday algorithms reproduce and multiply our cultural biases on a global scale.Anthropocentrism, humanistic supremacy and individualistic territorialism are rampant, making us all less humane.Society awakes slowly from the modern illusion of categorical identities and divides that keep nature from culture, human from animal, environment from embodiment, technology from biology and arts from science and society.The argument here is for taking stock of ways of cyborg knowing-also beyond the academic confines.It is time for new knowledge integrations forged in intellectual generosity.The cyborg, as a discipline-crossing figure, proposed theorypractices and practice-theories for how to readjust our high consumption, high energy and hyper-instrumental society, and ourselves, adaptively.In this piece, I proposed that feminist STS and cyborg knowing work as a prominent entry into the transformative multiverse of feminist posthumanities in practice.A
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".