Transformation through transdisciplinary practice: cultivating new lines of sight for urban transformation
Bibliographic record
Abstract
In this editorial introduction, we introduce the special issue "Transforming Urban Sustainability", which seeks to understand the pursuit and practice of transformative change for urban sustainability.Uniquely, the contributions to the Special Issue were developed through transdisciplinary collaborations and in this editorial we reflect on these practices and consider how they can catalyze transformative change in and through academic practice.We also review existing conceptual approaches to transformation and develop a heuristic device that helps us to appreciate its multiple and diverse dimensions.Through this heuristic, we generate lines of sight through which to view transformation and position the contributions in the Special Issue in relation to these.We conclude by suggesting that to advance both the understanding and traction of transformative action we need to recognise its multiplicity and actively engage with its different facets.
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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 | 0.018 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.027 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.004 | 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".