Ethics for endtimes MittigaRoss, <i>Climate Change as Political Catastrophe: Before Collapse</i> , Oxford University Press: Oxford, 2024; 176 pp. ISBN: 9780192868879, £80.00 (hbk)
Bibliographic record
Abstract
As the planet warms and the death toll mounts, frustration with democracy's pace has mainstreamed support to reject it, with some political theorists at work to normatively undergird extremist approaches. Such arguments demand careful scrutiny, as they risk providing dangerously misleading rhetorical tools for the naïve or nefarious political entrepreneur. This article critically engages Ross Mittiga's Climate Change as Political Catastrophe: Before Collapse as an object lesson. Mittiga argues looming climate catastrophe justifies authoritarianism: i.e. preventing catastrophe through authoritarianism is necessary if we do not promptly change course. Yet once the ingredients of “necessity” are unpacked with rigor not rhetoric, Mittiga's claims fail every step of a necessity test, leaving little on which to ground his authoritarian claims. The book illustrates the dangers of apocalyptic framing in normative argument, the pitch of which can distract readers from facts, logic, and salient contexts. Such arguments easily stack the moral deck for dangerously irrational solutions
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.017 | 0.006 |
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".