Posthumanist Perspectives on Racialized Life and Human Difference Pedagogy
Bibliographic record
Abstract
Abstract This discussion begins from the speculation that evaluating formulations of life has become one of the leading prerogatives of “novel” turns to matter, materiality, and the posthuman. However, moving with the Other (rather than simply representing them) has proven a difficult task for scholars in education concerned with decolonizing pedagogies by critiquing epistemological and ontological regimes of power disengaged from the interrogation of the metaphysics of race and sex at the center of Western metaphysical foundations of thought. There is an ongoing need for sustained engagement with the assumption of human primacy that runs through the nearly ubiquitous assertions of what Claire Colebrook calls active vitalism, which is characteristic of humanist approaches to education. In other words, the new conceptualizations of posthumanism only rarely challenge the lingering humanist concept of life itself. In this article, Petra Mikulan and Adam Rudder argue that posthumanist and neo‐vitalist materialist approaches to ontology must consider that racism is vitalist in the active sense because it begins with bodies (as bounded organisms always autopoetic and self‐proximate) and that vitalism is racist because it then distributes and discriminates racialized bodies according to their function as parts in a whole.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.063 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".