Bibliographic record
Abstract
Using Édouard Glissant's concept of creolization as a lens, this article explores how different senses of time respond to the volatile affective dynamics of polycrisis. It begins by specifying two interrelated problems: first, what it calls the affective double bind that intensifies desire for normalcy and familiarity when what is needed is creative and transformative thought and action; second, what it calls the pluriversal challenge of realizing planetary independence without imposing or privileging any single exclusive hegemonic meaning system. The paper then draws on Kyle Whyte's Anishinaabe informed “time as kinship” and Kyoto school philosopher Nishida Kitarō's “everyday eschatology” as examples for articulating “relational time,” contrasting this with a more familiar sense of “clock time” common to industrialized life. The article argues that cultivating relational time is helpful for navigating the affective dynamics of polycrisis and climate change. This is primarily discussed in terms of how it shifts engagement with conceptions and stories of origin and end, enabling a manner of maintaining their important affective work while challenging dominant habits of conceiving them through a logic of mutual exclusion that elevates one as the only real possibility. This amounts to a creolizing of eschatology.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.046 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".