Doubt and denial: epistemic responsibility meets climate change scepticism
Bibliographic record
Abstract
The analysis in this essay is indebted to the analysis of climate change scepticism developed in Naomi Oreskes’s and Eric Conway’s Merchants of Doubt where they expose the vested interests that produce a degree of doubt with respect to climate change science. The argument addresses the appeal to an inflated conception of human freedom – Liberty – that is allegedly threatened by injunctions to control pollution in the interests of ecologically conscious behaviour across a range of human practices of consumption. The essay draws on and advocates rethinking issues about epistemic responsibility and testimonial injustice in working toward developing ecologically informed climate change advocacy. El análisis de este ensayo está influenciado por el análisis sobre escepticismo ante el cambio climático desarrollado por Naomi Oreskes y Eric Conway en Merchants of Doubt, donde exponen los intereses creados, que producen un grado de duda en relación a la ciencia del cambio climático. El argumento se refiere a la apelación a una concepción exagerada de la libertad humana - la Libertad - , presuntamente amenazada por medidas cautelares para controlar la contaminación en los intereses de la conducta ecológicamente consciente a través de toda una gama de prácticas humanas de consumo. El ensayo se basa en, y aboga por repensar las cuestiones acerca de la responsabilidad epistémica y defiende replantear las cuestiones acerca de la responsabilidad epistémica e injusticia testimonial en el trabajo hacia el desarrollo ecológicamente informado de la defensa del cambio climático. DOWNLOAD THIS PAPER FROM SSRN: http://ssrn.com/abstract=2247830
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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 | 0.021 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.097 |
| Scholarly communication | 0.013 | 0.022 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.011 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".