Collective urban gardens: growing, learning and fostering social engagement
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scholars have recently worked to broaden the definition of urban engagement in order to better understand the multiple manifestations of this concept. Some, interested in grasping the potential transformative or demonstrative effects of everyday actions in urban settings, have examined active practices, such as gardening. Others have focused on the scale of action and have demonstrated how limited activities can have significant effects on individuals and communities. Building on the case studies of collective gardens in the significantly different urban settings of Québec City (Canada) and Madrid (Spain), we explore how the practices of urban gardening offer forms of learning that often go beyond gardening itself and expand into collective decision making and social engagement. The gardens we look at are grassroots based, have been in operation for approximately ten years and receive a form of support from city programmes. Our results show that these gardens are the sites of social processes where gardeners develop a strong identity in relation to the alternative lifestyles that they build, as well as a sense of belonging that goes beyond the boundaries of their garden and that connects them to nature. By developing their ethos of care, gardeners learn that neighbourhood-oriented actions have political implications that can help change the city.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it