Affirmative Ethics in the COVID-19 Moment: Perplexities, Paradoxes, and Surprises
Bibliographic record
Abstract
Posthumanism locates, progresses, and asserts knowledge in the openings for interconnection. In this article, we undertake a collective biography using an interconnected arts-based practice that affords us complex relations with each other and material ways of thinking and being together. With a shared interest in posthuman theory and memory work, the authors connected online from Aotearoa/New Zealand, Australia, and South Africa to address the question: What can we learn about the perplexities, paradoxes, surprises, and frustrations associated with our academic work during COVID-19? Using an arts-based methodology and a cartographic analytical approach for our critical posthuman research, our assemblage charted the power relations operating in and immanent to the construction and circulation of academic knowledge during COVID-19.
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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 | 0.022 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.018 | 0.096 |
| Scholarly communication | 0.015 | 0.013 |
| Open science | 0.001 | 0.014 |
| Research integrity | 0.003 | 0.007 |
| 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".