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Record W4403764097 · doi:10.24908/pceea.2023.17077

Identifying the foundation: Connecting codes of ethics, accreditation, values, and social justice to the engineering curriculum

2024· article· en· W4403764097 on OpenAlexaffvenueabout
Russell Kirkscey, Julie Vale, Jennifer Howcroft

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of WaterlooUniversity of Guelph
Fundersnot available
KeywordsAccreditationCurriculumFoundation (evidence)Engineering ethicsEthical codeSocial justiceSociologyEngineeringPolitical sciencePedagogyLawSocial science

Abstract

fetched live from OpenAlex

Canadian Engineering Accreditation Board (CEAB) graduate attributes are at the foundation of engineering curricular change in Canada. While CEAB graduate attributes require an understanding of ethics, professionalism, and impact, outcomes explicitly associated with equity, diversity, inclusion, indigeneity (EDI-I) and social justice broadly construed are absent. At present, the CEAB ethics criteria imply that understanding and valuing the code of ethics adequately addresses the issue, which leaves a gap in guidance for educators and curriculum designers. This paper reports on a thematic analysis of the 12 Canadian engineering codes of ethics and associated guidelines to discover the values overtly addressed or implied in the documents. We then map these findings onto the values of EDI-I and social justice as outlined by engineering scholars, and we offer recommendations for using the results to guide engineering instructors who want to make appropriate curriculum modifications that will support the CEAB efforts to address these movements.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.180
Threshold uncertainty score0.628

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.251
Teacher spread0.240 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations1
Published2024
Admission routes3
Has abstractyes

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