A Truth That Can Save Us? On Critical Theory, Revelation, and Climate Change
Bibliographic record
Abstract
In this article, I perform an experimental discussion of questions concerning revelation and truth in relation to the climate crisis. The concern is not revelation in any determinate theological sense but rather an attempt to reach for a perspective on truth that understands it as something that ruptures and disturbs the way we tend to think. I take my point of departure in a series of thinkers such as Horkheimer, Adorno, and Foucault. The key turn of the argument, however, is to confront the critical theoretical discourse of these thinkers with Schelling’s notion of positive philosophy, which offers an interesting alternative perspective on the question of existence and truth compared with standard forms of critical theory. In view of Schelling’s positive philosophy, I argue that his reflection on revelation is meaningful to revisit in relation to the climate threat, and I make some experimental connections between this idea of positive philosophy and recent discussions about the Anthropocene, asking for a more profoundly self-critical approach to question how we can approach the dire problems that we face as humanity. I end with an example of such reflection in the writings of the feminist materialist Nancy Tuana.
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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 | 0.018 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.008 | 0.076 |
| Scholarly communication | 0.007 | 0.015 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".