From reductive to generative crisis: businesspeople using polysemous justifications to make sense of COVID-19
Bibliographic record
Abstract
Both lay understandings of crisis moments and influential psychological models of cognition in times of uncertainty emphasize how crises limit thinking. Conversely, scholars as diverse as Foucault, Swidler, Bourdieu, and Butler have elaborated generative conceptions of crisis, which specify crises as moments of change, transformation, and heightened cognition. The research presented here takes up the question of how crises become thinkable, as actors gradually make sense of a newly uncertain context. Against a backdrop of polarization on the topic, in-depth interviews with 60 businesspeople navigating the coronavirus pandemic show that they see public health and economic well-being as interrelated. This has important effects on how businesses interpret and implement government directives and public health guidelines, from choosing to close before being mandated to do so, to staying closed even when allowed to reopen. Taken together, these findings substantiate generative models of crisis while drawing attention to the polysemous justifications elaborated by actors as they navigate shifting cultural and social scaffoldings.
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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 | 0.013 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.008 | 0.058 |
| Scholarly communication | 0.012 | 0.020 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.008 |
| 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".