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Record W6907210478 · doi:10.20381/ruor-27612

A Holistic Civil Engineering Approach to Accessibility: Addressing Systemic Barriers in the Built Environment

2022· other· en· W6907210478 on OpenAlexaboutno aff

Bibliographic record

VenueuO Research (University of Ottawa) · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBuilt environmentCurriculumEngineering educationIntersection (aeronautics)Civil engineering softwareAquatic and environmental engineering

Abstract

fetched live from OpenAlex

Civil engineers have many responsibilities to the public, among them designing safe, efficient, and reliable structures and infrastructure. But what is the responsibility of civil engineers towards ensuring that intended users can use these structures and infrastructure without encountering barriers? This research looks at the intersection of universal design (UD) and civil engineering to find if civil engineering students should learn about accessibility and UD during their undergraduate education and if civil engineering professionals should be held accountable when barriers are designed and constructed into the built environment. To answer these questions a survey was distributed to 222 building design professionals to gather their opinion and experience on the subject. Results show that civil engineers have limited knowledge of UD and accessibility requirements in the built environment and that they overwhelmingly believe that students should learn about these subjects during their civil engineering education. Furthermore, most participants agree that civil engineers do have a responsibility to ensure that the built environment is accessible to everyone. Based on the survey results, it is recommended to integrate a course about accessibility and UD in civil engineering curriculums. The curriculums of undergraduate civil engineering programs at Canadian universities were analyzed and it was found that no course discussing these subjects currently exists, but that there is space to implement them in a broader “social impacts of civil engineering” course. It is recommended that the CEAB recognizes accessibility and UD as useful and necessary subjects of education for civil engineering students. Finally, case studies of recent accessibility assessments of buildings are presented. It was found that while progress is being made in designing and constructing accessible structures, many are still not meeting all possible UD recommendations. The participation of professional civil engineers who have learned about accessibility and UD during their civil engineering education could improve the outcome of these projects. The findings of this thesis indicate that it is time to acknowledge civil engineers’ responsibility towards society and the need for a consistent approach to education about its social impacts, in particular about accessibility and universal design.

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)0.003
metaresearch head score (Gemma)0.003
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: Methods · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0030.010
Scholarly communication0.0060.005
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.111
GPT teacher head0.316
Teacher spread0.205 · 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
GenreMethods

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
Published2022
Admission routes1
Has abstractyes

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