“Got to get ourselves back to the garden”: Sustainability transformations and the power of positive environmental communication
Bibliographic record
Abstract
As places that disrupt “business as usual,” community food gardens carry the potential to experientially, critically, and restoratively recenter food systems and interconnected sustainability knowledges. Using interdisciplinary theory and practice-based observation, we zero in on the environmental planning and management space of the university campus to interpret how food gardens may not only materially change the campus landscape at a grassroots level but also act as constitutive forms of positive environmental communication. In doing so, food gardens may help realign the environmental premises of the university. At a time when universities have pressing leadership roles in rethinking the ecocultural, political, and economic dimensions of sustainable transformations of life as a whole, we illustrate how the creation of food gardens on all campuses might meaningfully and relationally reconnect university communities with the land where they work, learn, and teach, and, in the process, experientially promote ecocentric identities and empower change-making.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.035 |
| Scholarly communication | 0.011 | 0.011 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".