Bibliographic record
Abstract
Fifty years after the emergence of warnings over the effects of the environmental impacts of industrialization and other conditions of a planet subjugated by humans, we are still entertaining discussions about the existence of the phenomena of climate change. Worse still, we have not checked the behaviors and conditions that exacerbate the rate of environmental destruction. Older people, particularly those who are economically vulnerable, are among those most at risk in disasters, including events resulting from climate change. By applying the "epistemologies of ignorance" outlined by Nancy Tuana, I attempt to understand the rooted ignorance that prevents acceptance of the environmental impact of human kind's unrepentant misuse of the world's natural resources and the refusal to curb the excesses that have lead to environmental damage that has had, and that will continue to have, dire consequences on the planet and for the most vulnerable denizens of Earth. Far from being a pessimistic project of abjection and despair, this article proposes that an examination of climate change denial can provide guidance for the development of a better counter-narrative.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".