WHAT ISN’T NEW IN THE NEW NORMAL: A FEMINIST ETHICAL PERSPECTIVE ON COVID-19
Bibliographic record
Abstract
This essay argues that dominant responses to the COVID-19 pandemic redouble disparities in vulnerability to harms because these responses simply attempt to return to conditions prior to the outbreak of the virus. Although the widespread impact of COVID-19 has made interdependence more vivid, the underlying sociocultural devaluation of vulnerability, relationality, and dependency has intensified structural inequalities. People who were already disempowered and disadvantaged have been consigned to even more precarious conditions. A feminist ethical perspective avows vulnerability, relationality, and dependency as conditions that are both unavoidable and central to life. Such a perspective thus provides insight into why some dominant responses to the virus are unjust and what more ethical and more socially just responses to the pandemic, which foster social health as well as physical health, might look like.
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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 | 0.023 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.089 |
| Scholarly communication | 0.013 | 0.012 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.007 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".