Bibliographic record
Abstract
The cascading crises of the novel coronavirus pandemic era are seen, by some observers, as the constitutive components of a broad “polycrisis.” It is a useful term, but, as some have pointed out, while it registers the fact of coinciding crises it does little to explain the interaction of those crises. Indeed, polycrisis is a misleading conceptualization of the pandemic era in part because the cascading character of the present crisis is a function of a shared ultimate cause. What we have been experiencing is best understood as a crisis of capitalism, the result of industrial humanity’s deformed relationship with the natural world. This is more specific than an obvious contending description that would render the present crisis in anthropogenic terms, as a result of human activity. Instead, the present crisis is the product of specific forms of human activity and particular elements of humanity, namely, capital. This being the case, we might speak instead of a broad, structural crisis that is, in turn, experienced as a crisis cascade. This “paradox of polycrisis” has historiographical implications, and this article concludes by suggesting how contemporary historians can confront the crisis and write history for our times.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.024 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| 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".