Sharing the Earth: Sustainability and the Currency of Inter-Generational Environmental Justice
Bibliographic record
Abstract
Philosophers often understand environmental sustainability as a duty of distributive justice between the generations of the earth. Since every generation is equally entitled to the bounty of the natural environment (the thinking goes) every generation should have a fair share of that bounty. But since generations precede each other in time, it is the duty of earlier generations to ensure that later generations receive their fair share. Acting sustainably is the way of meeting this duty, since sustainable practices are those that (ideally) preserve the environment for the future. But what is a ‘fair’ share of something as complex, varied and dynamic as ‘the environment'? How are we to value nature for the purposes of measuring ‘shares’ of it? I think the answer to these questions lies in the difference between sharing something by parts, like a pie, and sharing something by turns, like a bicycle. The generations share the earth by turns, not by parts, and so questions about fairness of shares are questions about turns, not parts. We need to ask what constitutes a ‘fair turn’ with the earth, and for that question we don't necessarily need to be able to commensurate the various parts of nature, just as we don't need to know the relative value of the parts of a bicycle to say what constitutes a fair turn with it.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".