MétaCan
Menu
Back to cohort
Record W1946664660 · doi:10.1139/cjfr-2015-0123

Building material preferences with a focus on wood in urban housing: durability and environmental impacts

2015· article· en· W1946664660 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Forest Research · 2015
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsApartmentBusinessProduct (mathematics)RespondentSustainabilityPopulationEnvironmentally friendlyArchitectural engineeringEngineeringCivil engineeringEcologyPolitical science

Abstract

fetched live from OpenAlex

As societies urbanize, a growing proportion of the global population and an increasing number of housing units will be needed in urban areas. High-rise buildings and environmentally friendly, renewable materials must play important roles in sustainable urban development. To achieve this, it is imperative that policy makers, planners, architects, and construction companies understand consumer preferences. We use data from urban dwellers in the Oslo region of Norway to develop an understanding of material preferences in relation to environmental attitudes and knowledge about wood. We emphasise wood compared with other building materials in various applications (structural, exterior, and interior) within urban apartment blocks. We use 503 responses from a web panel. Our findings show that Oslo area consumers tend to prefer materials other than wood in various applications in apartment blocks, especially structural applications. Still, some respondent prefer wood, including some applications in apartment blocks where wood is currently not commonly used. The best target for wood-based urban housing includes younger people who have strong environmental values. As environmental attitudes evolve in society and a greater proportion of consumers search out environmentally friendly product alternatives, the opportunities for wood to gain market share will most likely increase.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.037
GPT teacher head0.279
Teacher spread0.242 · 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