Subtle potentials as emancipatory forces? Recasting the micropolitics of risk and disaster management
Bibliographic record
Abstract
Drawing on the philosophy of movement and processes, the theory of attention and critical disaster and risk studies, this paper explores how the ways of dealing with alterity such as volcanic toxicity involve enacting the emergence of subtle potentials. These subtle potentials are moments of pure transformation in which alternatives to an inescapable and homogeneous future are realised while their subtle nature brings them into the periphery of our collective and personal attention. Influenced by the work of cultural theorist Yves Citton, the paper argues that subtle potentials are activated through a modality of free-floating attention that allows those confronted with hazards and risk to reorient their focus through different rhythmic processes that distort the fatality of permanent volcanic emissions (PVEs). Building on these conceptual relations, the paper draws on three interrelated rhythmic tales that help us understand how these subtle potentials emerge and are intertwined in the wider fabric of a micropolitics of spatio-temporal displacement, which in turn helps us recast those seen as vulnerable to PVEs as vibrant political actors of the everyday. The paper concludes by highlighting the relevance of subtle potentials when working with communities affected by hazards and risk and argues for a more complex understanding of the processes involved in shaping the micropolitics of risk and disaster management.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.055 |
| Scholarly communication | 0.009 | 0.017 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".