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Record W4384571381 · doi:10.5334/bc.333

Transition to a regenerative future: a question of time

2023· article· en· W4384571381 on OpenAlexaff
Raymond J. Cole

Bibliographic record

VenueBuildings and Cities · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicSustainability and Climate Change Governance
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMainstreamRelevance (law)Set (abstract data type)Engineering ethicsArchitectural engineeringBusinessRisk analysis (engineering)Computer scienceEngineeringPolitical science

Abstract

fetched live from OpenAlex

This paper explores the difference between the ways that nature functions and the way that the built environment is currently produced and operates, and if and how they can be realigned. While regenerative approaches can apply to a range of human enterprises, the paper focuses on their application to the production of the urban built environment. It examines if and how they may move into mainstream building practice and how long this may take given the inherent inertias in the building industry. Key issues include the recasting and interrogating of the accumulated knowledge held by design professionals within a broader living systems frame, and rethinking what constitutes a successful outcome of building design. Such efforts are set against the diminishing time available before a series of climate tipping points are crossed and further short- to mid-term constraints posed by a host of other powerful countervailing forces. Practice relevance A critique of emerging regenerative practices is provided with an overview of both the challenges facing design professionals moving them into mainstream building practices, and the opportunities it provides them. Rather than viewing their work as solely reducing environmental impact, regenerative practices offer architects and planners a positive casting and expansion of their responsibilities. They enable design professionals to both contribute in the bringing about of systems-level change and to provide inhabitants with greater opportunities and pathways to both navigate an uncertain future and re-establish, reconnect and co-evolve with natural systems.

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)0.015
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0110.063
Scholarly communication0.0160.033
Open science0.0020.014
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0130.001

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.

Opus teacher head0.008
GPT teacher head0.222
Teacher spread0.215 · 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 designTheoretical or conceptual
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

Citations3
Published2023
Admission routes1
Has abstractyes

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