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Record W2909078169 · doi:10.24908/pceea.v0i0.12963

Humanitarian Engineering: A New Interdisciplinary Course on the Application of Engineering Skills to Local and Global Humanitarian Challenges

2018· article· en· W2909078169 on OpenAlexaffvenue
Andrew Sheroubi, Gabriel Potvin

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2018
Typearticle
Languageen
FieldEngineering
TopicBiomedical and Engineering Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDeliverableGeneral partnershipCourse (navigation)SustainabilityCurriculumEngineering ethicsWork (physics)Engineering educationEngineeringEngineering managementPolitical scienceSociologyPedagogySystems engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Many students express a desire to apply their technical engineering skills to produce positive societal impacts, and although sustainability frameworks do take this into consideration in traditional engineering curricula, there are relatively few avenues for students to work on real global social issues during their undergraduate studies. This paper describes a new interdisciplinary course developed at UBC on the use of engineering skills to solve humanitarian challenges.The course is composed of case-study analyses, interactive activities and simulations, group discussions and seminars, and a technical design project completed in partnership with an NGO or charity working on a particular humanitarian challenge. The rationale and design of the course and its deliverables, as well as student feedback on this first iteration of this course are presented.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.023
Threshold uncertainty score0.078

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.002
Scholarly communication0.0050.002
Open science0.0020.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0230.008

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 head0.006
GPT teacher head0.214
Teacher spread0.208 · 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 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

Citations6
Published2018
Admission routes2
Has abstractyes

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