Leading change from the inside-out : negotiating the psycho-social in sustainability engagement
Bibliographic record
Abstract
This study explores how sustainability practitioners understand and engage with the subjective psychological dimensions of `social mobilization'. At this particular moment, there exists scant research into precisely how these dimensions are being theorized and incorporated into the practice of social mobilization, despite a growing recognition that environmental engagement necessarily involves the `inner life' of people--the complex and interconnected psycho-social influences on who we are and how we understand our world. Using a narrative methodology, I interviewed seven sustainability facilitators about how they are currently making meaning of social change and how subjectivity is represented within this. The analysis presents four distinct ways that psycho-social dimensions are being negotiated and related to in engagement work. This research indicates that being able to engage with subjectivity is not so much a technical skill that can be learned, but rather a new way of making meaning of the world, others, and oneself.
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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 | 0.020 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.031 | 0.113 |
| Scholarly communication | 0.024 | 0.021 |
| Open science | 0.003 | 0.034 |
| Research integrity | 0.006 | 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".