Pandemic Life-lines: A Multimodal Autoethnography of COVID-19 Illness, Isolation, and Shared Immunities
Bibliographic record
Abstract
As a crosscutting concept in biology, anthropology, and philosophy, immunity has been a critical ‘site’ of debate on the relations between self and other, organism and environment, risk and responsibility, the corporeal and the political. In this Research Article, I trace how these relations and everyday life during the COVID-19 pandemic relied on a web of coordinated—and sometimes unexpected—lines of communication, restriction, and solidarity. Using an experimental approach that combines multimodal autoethnography and multiscalar relational analysis, I present a first-person account of travelling during, testing for, and falling ill and isolating with COVID-19 in late 2021. I explore how pandemic life-lines, including public health measures, vaccinations, devices, and helplines, as well as mundane gestures of care and ecologies of support, acted together as shared immunities. In this exploration, I propose to reconceptualise ‘immunity’ as a process network rather than a defence apparatus, shedding light on how these life-lines may influence differential trajectories of disease and healing. To conclude, I discuss how my conceptual and methodological approach contributes to a social ecological understanding of immunity, that goes beyond the biopolitical, in times of pandemic and in the future.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 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".