Bibliographic record
Abstract
The prominent Australian earth scientist, Tim Flannery, closes his recent book Here on Earth: A New Beginning with the words “… if we do not strive to love one another, and to love our planet as much as we love ourselves, then no further progress is possible here on Earth”. This is a remarkable conclusion to his magisterial survey of the state of the planet. Climatic and other environmental changes are showing us not only the extent of human influence on the planet, but also the limits of programmatic management of this influence, whether through political, economic, technological or social engineering. A changing climate is a condition of modernity, but a condition which modernity seems uncomfortable with. Inspired by the recent “environmental turn” in the humanities—and calls from a range of environmental scholars and scientists such as Flannery—I wish to suggest a different, non-programmatic response to climate change: a reacquaintance with the ancient and religious ideas of virtue and its renaissance in the field of virtue ethics. Drawing upon work by Alasdair MacIntyre, Melissa Lane and Tom Wright, I outline an apologetic for why the cultivation of virtue is an appropriate response to the challenges of climate change.
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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.010 | 0.023 |
| Insufficient payload (model declined to judge) | 0.003 | 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".