“Doing Hope”: Ecofeminist Spirituality Provides Emotional Sustenance to Confront the Climate Crisis
Bibliographic record
Abstract
Environmental crises caused by our changing global environment evoke intense and difficult emotions, particularly the paralysis that often results from despair. Understanding how people who are deeply engaged in environmental activism deal with their emotions can help in emotionally equipping people to address the climate crisis. Ecofeminist spirituality directly addresses these issues through an environmental stewardship that offers hope and healing for the world. This study includes 14 interviews with workers at an ecojustice center founded by an order of Catholic sisters in the United States. We used thematic analysis to identify three main themes that collectively describe the participants’ perspectives on (a) experiences of difficult feelings, (b) strategies for coping with those feelings, and (c) perspectives on cultivating hope. Participants shared how they were able to cope with difficult emotions and cultivate hope that the work they are doing matters, which was essential to sustaining their ecojustice work. As social workers respond to the changing environment, understanding how to sustain environmental work at the macro-level is essential to addressing largescale problems while also attending to difficult emotions at the microlevel. Further implications for social work practice include the importance of intergenerational organizing, living in “right relationship,” incorporating spirituality, and reinhabiting the profession.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".