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Record W4413029318 · doi:10.1007/978-3-031-84367-9_1

A Methodological Framework for Transdisciplinary Urban Planning

2025· book-chapter· en· W4413029318 on OpenAlex
Du Toit, Amy Pieterse, Sandile Mbatha

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSustainable development goals series · 2025
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsEnvironmental planningManagement scienceSociologyRegional scienceEngineering ethicsComputer scienceGeographyEngineering

Abstract

fetched live from OpenAlex

Abstract Urban planning research is challenged by combining scientific rigour with societal relevance, especially in terms of urban sustainability at local government level. Transdisciplinarity aims to combine rigour with relevance. But how should urban planning researchers, practitioners and other stakeholders collaborate and conduct transdisciplinary research? This chapter reviews the literature on transdisciplinarity for urban sustainability and, instead of advocating specific methods, presents a holistic and flexible methodological framework. The heuristic framework serves to help stakeholders navigate transdisciplinarity and make more considered decisions when conducting transdisciplinary research for urban planning. Practitioner reflections on the framework are provided using the example of Planning Support Science and a customised Planning Support System for climate resilient planning at the local government level in South Africa.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.477
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.089
GPT teacher head0.315
Teacher spread0.226 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it