Burden-sharing in a Changing Climate: Which Principles and Practices can Theologians Endorse?
Bibliographic record
Abstract
Empirical evidence of our changing climate is frequently interpreted through the lens of either optimism or pessimism. In tandem with this, ethical responses can oscillate from myopic ‘business as usual’ to misanthropic ‘lifeboat ethics’. In this paper I argue that these are inadequate and unworthy positions from which to begin in Christian ethics. The question of sharing the burdens of climate-change mitigation and adaptation is the crucial task facing the world community. The development of the burden-sharing rules—sector based as well as country based—since the Kyoto agreement will be evaluated from the perspective of three theological ethical principles: justice, solidarity and subsidiarity. Lastly I suggest that creation serves as a ground for developing shared perspectives in the ethics of environmental questions in the context of intercultural and interfaith dialogue.
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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 | 0.054 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.115 |
| Scholarly communication | 0.020 | 0.030 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.011 | 0.013 |
| Insufficient payload (model declined to judge) | 0.002 | 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".