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Record W4408829830 · doi:10.3390/su17072921

Housing Design for Circular Economy and Sustainability

2025· article· en· W4408829830 on OpenAlexaff
Avi Friedman

Bibliographic record

VenueSustainability · 2025
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsMcGill University
Fundersnot available
KeywordsCircular economySustainabilitySustainable designBusinessEconomicsEconomic systemArchitectural engineeringEngineeringEcology

Abstract

fetched live from OpenAlex

The purpose of this paper is to explore the possibilities of bringing house development to a more sustainable and ecological level using the idea of the circular economy (CE) in the construction industry. Housing is an essential aspect of the economy and the building industry. The development of this sector is driven by an increasing urban population and the need to modernize existing residential buildings. Contemporary home situations should address reducing their detrimental impact on the natural environment. This is achievable by minimizing the consumption of natural resources and construction waste. This assumption is part of the core CE work, which allows for the recirculation of building materials. To discuss the underlying topics, this assumption was explored by employing a non-reactive desk research method. The review of scientific articles and studies covered the following topics: (i) the definition of CE, (ii) the shearing layers concept in building, and (iii) design for disassembly (DfD) in home construction. The second stage of evaluating the project “Domus Ex Machina” includes the following: (i) modular dimensions, (ii) prefabricated production, and (iii) adaptive designs and systems. In the discussion, this research identified several barriers to efficient CE adoption in the construction industry. The discussion highlights potential impediments to the application of the CE in housing contexts, including (i) storage and logistics issues, (ii) cost concerns and implementation challenges, (iii) policy inconsistencies across regions, and (iv) market demand and supply chain restrictions. The final paper conclusions demonstrate the significance of implementing the CE idea in housing building, hence reducing the negative impact on the environment.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.897
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.260
Teacher spread0.251 · 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 teacher head, not a consensus.

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

Citations8
Published2025
Admission routes1
Has abstractyes

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