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Record W1900796572 · doi:10.24908/pceea.v0i0.4876

Design for Inclusion - A Roundtable DIscussion

2013· article· en· W1900796572 on OpenAlexfundvenueaboutno aff
Catherine Mavriplis

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicInnovative Approaches in Technology and Social Development
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsInclusion (mineral)BrainstormingCurriculumGovernment (linguistics)PortfolioEngineeringCorporationManagementTheme (computing)Library scienceEngineering ethicsSociologyPedagogyPolitical scienceComputer scienceSocial science

Abstract

fetched live from OpenAlex

We propose a roundtable discussion on “Design for Inclusion” and how to integrate this concept into the undergraduate engineering curriculum. Designing devices and technology that benefit and are useful to all members of society and take into account diverse users' needs does not seem to be a common practice in industry nor in the classroom. We all know examples of devices that seem to have “missed the point” for large segments of their user base. We believe diverse teams are needed to brainstorm ideas from the start and to bring such products to market. The revolution in thinking needs to start at the source, where students are being educated. How can “design for inclusion” become integrated into our design education? The panelists who will discuss this theme will be: • Beth Kolko, Associate Professor in the Dept of Human Centered Design & Engineering, University of Washington, USA (confirmed) • Benoit Gervais, Design engineer, Principal, Futurescape, Ottawa (confirmed) • Elizabeth Croft, Professor of Mechanical Engineering, University of British Columbia (confirmed) • Li Shu, Associate Professor of Mechanical and Industrial Engineering, University of Toronto (confirmed) • Sarah Shortreed, Vice-President, Enterprise Portfolio Management, BlackBerry, Research in Motion (confirmed) • Antony Hodgson, NSERC Chair in Design Engineering, University of British Columbia (confirmed) The panel will be moderated by Catherine Mavriplis, University of Ottawa. We invite the community to join in the discussion with the panelists. These could include representatives of Engineers Canada, the licensing bodies, other NSERC Design Chairs, Deans and Curriculum Chairs, professors and students, industry and government.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.376
Threshold uncertainty score0.834

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 studies0.0010.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.203
Teacher spread0.190 · 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

Citations0
Published2013
Admission routes3
Has abstractyes

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