Disaster or Sustainability: The Dance of Human Agents with Nature's Actants*
Bibliographic record
Abstract
Cet article défend une recherche sociologique qui allie le meilleur du constructionisme social avec le réalisme critique, et qui intègre la sociologie des catastrophes à la sociologie environnementale. Il montre comment les perceptions de la gestion des catastrophes sont socialement construites au moyen d'une action communicative dans un contexte d'incitations venant des ≪ actants≫ de la nature, comment les autorités sont tentées de remplacer la transparence par le secret quand ces incitations deviennent particulièrement dangereuses et comment les catastrophes sont utilisées a d'autres fins. La tempête de verglas de Janvier 1998, qui donnait l'impression d'etre une catastrophe naturelle (la plus dispendieuse de l'histoire canadienne), était plutôt un hybride déclenché par des constructions de la nature primale qui sont devenues désastreuses où la nature recombinante vulnérable est devenue socialement construite. This paper argues for sociological research that combines the best of social constructionism and critical realism and that integrates disaster sociology with environmental sociology. It documents how perceptions of managing disaster are socially constructed through communicative action in a context of prompts from nature's actants, how authorities are tempted to replace openness with secrecy when those prompts become particularly dangerous, and how disasters are used for other purposes. The January 1998 ice storm that seemed a natural disaster (the most expensive in Canadian history) was instead a hybrid initiated by primal nature's constructions that became disastrous where vulnerable recombinant nature had been socially constructed.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".