Embodying Theology: Trauma Theory, Climate Change, Pastoral and Practical Theology
Bibliographic record
Abstract
Since 2009, the amount of literature focused on the psychological and social dimensions of the climate crisis has increased exponentially. This growing interest in the topic is signaled especially in the American Psychological Association (APA)’s multiple reports on the mental health impacts of climate change. More recently, across different disciplines, links have also been made between trauma theory and the climate crisis. These rich discussions include overlapping concerns, areas of potential fruitfulness and theological implications for all the practical theological disciplines, especially for pastoral theology and practices of care. Given the implicitly existential, theological and spiritual dimensions embedded in the realities of both trauma and the climate crisis, there is an important opportunity for pastoral theology in particular, and practical theology more generally, to engage, learn from and contribute to the interdisciplinary conversation. In this paper, I first offer a brief overview of the literature in pastoral theology related to the climate crisis. Second, I present literature specifically on trauma theory and the climate crisis, outlining several of the key themes emerging across the interdisciplinary discussion. Third, I reflect theologically on the presented content, discussing and drawing forward areas of theological, epistemological and practical fruitfulness for practical and pastoral theology.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.006 | 0.042 |
| Scholarly communication | 0.009 | 0.012 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 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".