The role of care in creating narratives for sustainability
Bibliographic record
Abstract
Narratives based on our capacity to care for others can foster more sustainable interactions in socioecological systems. This article explores the role of care in the stories that we tell about ourselves and how these stories shape our relationship with the more-than-human world. It offers a framework for tilting narratives presenting human nature as self-centered and extractive toward ones characterizing humans as caring and other oriented, aiding the transition to a more sustainable basin of attraction. We bring into dialogue narrative psychology, narrative therapy, ethics of care, and complex adaptive systems theory. Based on this, we propose a framework that can aid in changing narratives in wider social–ecological systems, which is composed of three synchronized phases: (1) identification of the problem and the story that supports it, (2) creation of possibilities for change, and (3) reinforcement of new scenarios. We apply this framework to the topic of consumption and propose that sustainable consumption can be constructed as an act of care rather than a sacrifice. We conclude by inviting readers to act on their concerns about caring for others and for the more-than-human world to strengthen and spread emerging narratives based on care.
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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 | 0.018 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.049 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".