Ethical risks of attenuating climate change through new energy systems: the case of a biofuel system
Bibliographic record
Abstract
It has been estimated that a quarter of global energy could be consumed by transport, accounting for approximately 25% of total carbon dioxide emissions.This provides opportunity to reduce emissions through alternative fuels.As a result, biofuels have recently become the focus of many climate change policy discussions.However, those produced from agricultural crops are not greenhouse gas neutral and have the potential to transform many of the earth's natural landscapes into monocultures.This land transformation leads to ethical trade-offs that should be addressed before policy is put in place.These trade-offs will likely result in competing social institutions with different values.A scientific approach to assessing ethics is too reductionistic to achieve a fair outcome.Normative ethical theory is discussed as a means to deal with competing values in a just manner.The Wide Reflective Equilibrium (WRE) process should be used to achieve the fairest policy.
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 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 | 0.026 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.039 |
| Scholarly communication | 0.011 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.017 | 0.013 |
| 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".