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Record W4410037838 · doi:10.3390/buildings15091528

“True” Accessibility Barriers of Heritage Buildings

2025· article· en· W4410037838 on OpenAlexafffund
S.E. Chidiac, Mouna A. Reda

Bibliographic record

VenueBuildings · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsMcMaster University
FundersAccessibility Standards CanadaMcMaster University
KeywordsArchitectural engineeringConstruction engineeringEngineeringForensic engineeringComputer science

Abstract

fetched live from OpenAlex

Heritage buildings, which symbolize the pride of a nation, were built prior to the development of current standards, including those for accessibility. As nations strive for equity, diversity, and inclusion, creating barrier-free environments, including heritage buildings, becomes imperative. This study aims to identify the “true” accessibility barriers of heritage buildings. Accordingly, a three-part study was conducted: review current standards and best practices; document and investigate the accessibility lived experiences of people with different abilities in heritage buildings; and analyze and discuss the data. The findings revealed that 19%, 17%, and 64% of reported “true” barriers per building were attributed to the conflict between accessibility and heritage preservation, accessibility standard clarity/specificity, and accessibility standard compliance, respectively. In comparison, accessibility-trained professionals attributed 16%, 39%, and 45% of their assessments to the same categories. A significant number of accessibility barriers in heritage buildings can be mitigated by applying current standards. The accessibility needs of people with cognitive/intellectual disabilities are the least addressed and understood by the standards and accessibility-trained professionals.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.930
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.262
Teacher spread0.217 · 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 designNot applicable
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

Citations7
Published2025
Admission routes2
Has abstractyes

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