Community perceptions of sustainability: (Re)framing what matters for more just, ethical, and liveable municipalities
Bibliographic record
Abstract
Municipal governments and community organisations are key stakeholders in the mobilisation of global Sustainable Development Goals (SDGs) through opportunities to make and implement sustainability policies at local levels. However, as perceptions of sustainability are normalised through globalising, colonial, neoliberal, and capitalist discourses, alternative stories of sustainability become marginalised. In response, this article positions diverse, contrasting, and often conflicting perceptions of sustainability within a relational assemblage to map the affects of difference between normalising and alternative perceptions of sustainability in local governance contexts of Saskatchewan, Canada. This article adopts cartographic and diffractive storytelling to map diverse perceptions of sustainability gathered through a series of focus groups and a Skills Forum event, as part of the Governing Sustainable Municipalities (GSM) project. By reading perceptions of sustainability through each other, economic, social, and environmental pillars of sustainability and diverse perceptions of sustainability from diverse stakeholders come into an entangled/differentiated relationship. As there is no central point of reference in a relational assemblage, heterogeneous perceptions of sustainability are held together through complex patternings of diverse, multiple, and often sticky, uneven knottings that dislodge hierarchical assumptions about what counts as sustainability. Providing an emplaced and situated account of perceptions of sustainability, we illustrate how municipal and organisational actors can transform through co-implicated relationships with social and material forces. To this end, assemblage thinking provides important anticolonial possibilities for sustainability policy making and implementation in the municipal sector.
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.
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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.016 | 0.048 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".