In the Kingdom of the Sick: Abjection, Mutuality, and the Afflicted in Recent Pandemic Fiction
Bibliographic record
Abstract
During a pandemic, the omnipresence of the virus dictates that we negotiate our proximity to illness. We are brought face-to-face with the abject (the infected, the dying, the dead) provoking disgust and fear, but also, significantly, recognition. Our initial (and sometimes violent) reaction reflects an entrenched refusal to recognize any similarity between ourselves and the abject. Quarantining and social distancing are proven and (somewhat) effective methods for containing the spread of disease, but they also solidify the distinction between the sick and the well. The drive for immunity – an exemption from that which threatens the community –is a salient feature of many contemporary pandemic fictions. At the same time, other works push against that impulse, accentuating the need for the communal – an assumption of mutual vulnerability. Authors of recent Covid-centric texts (Gary Shteyngart, Elizabeth Strout, Weike Wang) illustrate how individuals oscillate between the contradictory desires for community and immunity – for being both a part and apart. In contrast, Sarah Hall’s Burntcoat and Ali Smith’s Companion Piece highlight the transformative possibilities of coming to terms with abjection and recalibrate the community/immunity balance in the light of present or future pandemics.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.017 | 0.054 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".