Exploring Social Sustainability Through Urban Gardening: A Participatory Rapid Realist Review
Bibliographic record
Abstract
Abstract Among the classic triad of sustainable development—ecology, economy, and society—social sustainability remains the least studied and critically evaluated. Conceptualizing wellbeing as a core component of social sustainability, this study explores how the social fabric of urban life, including third spaces, influences the wellbeing of older residents. Using a Participatory Rapid Realist Review (PRRR) methodology, co-designed with Pendrellis Housing Society, this research synthesizes peer-reviewed literature and integrates community-based perspectives to examine how urban gardening as a mechanism for developing engaging third places contributes to social sustainability. The PRRR approach investigates why, how, and under what circumstances urban gardening supports wellbeing. It follows a six-step process: (1) defining the review scope, (2) identifying relevant studies, (3) synthesizing data, (4) engaging stakeholders, (5) validating findings, and (6) disseminating results. Recognizing the complexity of linking urban gardening to wellbeing, this research takes a reflexive approach, embedding subjective perspectives within the analysis. Focusing on urban-dwelling older adults, gardening, and wellbeing, findings highlight the significance of small-scale social practices within third places that create vibrancy in urban life. Given the diversity of housing arrangements and motivations for gardening, understanding social sustainability at a micro scale is essential. Through community-engaged scholarship, older adults actively contributed to a co-designed Theory of Change, ensuring findings are grounded in lived experiences and applicable across the life course. Ultimately, this collaboration supported the development of an onsite community garden, ensuring older adults’ voices shaped both the research process and its practical application.
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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 | 0.084 | 0.177 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.016 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".