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Record W1956706698 · doi:10.24908/pceea.v0i0.4834

ENGINEERING LEADERSHIP IN POSITIVE SPACE

2013· article· en· W1956706698 on OpenAlexaffvenueabout
Peter Weiß, Lesley Mak, Susan McCahan, Jason Bazylak

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPrideParadeQueerSpace (punctuation)LesbianEngineering educationComicsEngineeringSociologyPsychologyMedia studiesGender studiesPolitical scienceLawComputer scienceMechanical engineering

Abstract

fetched live from OpenAlex

Two years ago, a satirical column in the Engineering undergraduate comic newspaper elicited complaints and the accusation of homophobia from the university community. Engineering students, faculty and staff responded with several initiatives to counteract being stereotyped as homophobic. The Lady Godiva Bnad (sic), which had always marched in the Toronto Gay Pride Parade, actually built a float and set off the cannon, winning the (perhaps only ever) Shock and Awe Award. Faculty members, staff and students formed an Engineering Positive Space committee and, with the student group, LGBTQase (Lesbian, Gay, Bisexual, Trans, Queer and Allies in Science and Engineering), developed a poster that raised awareness of the diverse sexuality of engineering students as well as an Engineering Positive Space badge with a unique "engineering" variation of the Positive Space rainbow triangle.

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)0.004
metaresearch head score (Gemma)0.006
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.030
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0300.020
Scholarly communication0.0120.004
Open science0.0010.016
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0180.002

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 head0.020
GPT teacher head0.196
Teacher spread0.177 · 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
GenreOther

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
Published2013
Admission routes3
Has abstractyes

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