The Temporal Politics of Inevitability: Mass Death during the COVID-19 Pandemic
Bibliographic record
Abstract
Abstract Many international phenomena, from complex, interconnected processes to specific catastrophes, have been deemed “inevitable” by elites, policymakers, and scholars. Yet existing scholarship treats “inevitability” as an objective fact to be assessed retrospectively, rather than an expression of politics and contestation. To see the “politics of inevitability,” we argue, requires attention to the underlying politics of time through which inevitability is narrated and naturalized. Drawing upon the “temporal turn” in IR, we identify three constitutive practices of inevitability: problem definition, designations of agency and responsibility, and distribution throughout a political community. Empirically, we illustrate our argument through a discourse analysis of how mass death was produced as “inevitable” (or not) during the first wave of the COVID-19 pandemic in Europe. The politics of inevitability does not cause the outcomes that are deemed inevitable, but through narrating time in a particular way, it provides the conditions in which certain policy choices become imaginable and/or desirable. This has vital implications for the ways that other future events are cast as inevitable, including climate change, war, and future pandemics.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".