Transformative capacity and local action for urban sustainability
Bibliographic record
Abstract
There is a consensus about the strategic importance of cities and urban areas for achieving a global transformation towards sustainability. While there is mounting interest in the types of qualities that increase the capacity of urban systems to attain deep transformations, empirical evidence about the extent to which existing institutional and material systems exhibit transformative capacity is lacking. This paper thereby seeks to determine the extent to which sustainability initiatives led by local governments and their partners reflect the various components that the literature claims can influence the emergence of transformative capacity as a systemic property of urban settings. Using an evaluative framework consisting of ten components of transformative capacity and associated indicators, the specific objective is to identify patterns in these initiatives regarding the presence of individual components of transformative capacity and their interrelations with other components. The analysis of 400 sustainability initiatives reveals thin evidence of transformative capacity. When detected, evidence of transformative capacity tended to emerge in relation to wider processes of institutional- and social-learning and initiatives that linked outcomes to a city-wide vision of planning and development. However, instances of such initiatives were rare. This widespread lack of evidence for transformative capacity raises concerns that this set of attributes normalised in the literature is in fact rarely found in sustainability action on the ground.
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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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.029 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".