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Record W6996718280

Studying the role of knowledge: How urban design knowledge has changed in the last quarter of a century

2015· other· en· W6996718280 on OpenAlexaboutno aff

Bibliographic record

VenueUWE Research Repository (UWE Bristol) · 2015
Typeother
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsnot available
Fundersnot available
KeywordsUrban designQuarter (Canadian coin)Work (physics)HappeningUrban planningSet (abstract data type)Relation (database)
DOInot available

Abstract

fetched live from OpenAlex

n 1992 A.V. Moudon published an article titled: “A Catholic Approach to Organizing What Urban Designers Should Know” where she introduced a set of categorisations that helps urban designers to organise their knowledge. After almost quarter a century, we try to update her initial article in order to find out how urban design knowledge has changed in response to the dramatic changes happening in the world. This study reflects on a broader topic of how the built environment-related knowledge and the role of universities have changed recently. In doing so, the range of literature that is being taught in more than 30 universities for urban design courses has been studied to see what is being understood as an important text, or topic. Different traditions of urban design pedagogy in US, UK and Australia have been derived by analysing these lists. A briefer enquiry has also been done to find out how urban design course coordinators see the change in urban design literature in relation to the mentioned article.The result of this research shows that the shared body of knowledge is now relying far more on mixed method and interdisciplinary methodologies especially in more global universities. The current challenge for education system is to adapt with the rapid change in technology and enabling students to work in non-western context. The final stage of the research suggest replacing traditional urban design teaching with more critical thinking that enables student to develop their own “theory” - as it is illustrated in the post-human condition, theory should happen at the same time with practice. As a consequence, organizing the knowledge will be more like navigation through the literature that happens based on the problems in hand.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.086

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.006
Science and technology studies0.0100.025
Scholarly communication0.0160.018
Open science0.0010.009
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0030.000

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 head0.099
GPT teacher head0.337
Teacher spread0.238 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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