Bibliographic record
Abstract
Many people working in the field of religion and ecology share a concern for peace in this world. For example, the geologian Thomas Berry wrote a poignant essay presenting his vision of the peace of the Earth, a Pax Gaia, which was published in his important book, Dream of the Earth (1988). In crafting a response to the ecological crisis, Berry repeatedly wrote with urgency about the need to rediscover and foster wonder amongst humans in relation to both the Earth and universe communities. Broadly taking these two features of Berry’s work as its jumping off point, this article unfolds select ways to couple wonder, the moral imagination and socio-ecological flourishing at a time of climate change and social unrest, in the service of substantive peace. Specifically, the authors offer a discussion of wonder as it can be understood from reading Berry’s work. Moving towards a contemporary contextual ethical application, this article then draws on the work of conflict transformation theorist and practitioner Jean Paul Lederach concerning the moral imagination, which he characterizes as the art and soul of building peace. The authors conclude by proposing a path towards an authentic Pax Gaia that broadens the scope of wonder to include more fully its human component, and broadens the scope of the moral imagination to include more fully its biological and geological components. It is in this way, this article suggests that we can foster an integral approach to peace, one characterized by socio-ecological flourishing.
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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.053 |
| Scholarly communication | 0.016 | 0.023 |
| Open science | 0.001 | 0.017 |
| Research integrity | 0.006 | 0.020 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".