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Record W4308803121 · doi:10.24908/pceea.vi.15836

Engineers Embracing Leadership: Making the World a Better Place through Data-driven Decision Making

2022· article· en· W4308803121 on OpenAlexafffundvenue
Cindy Rottmann, Andrea Chan, Jessica Li, MacKenzie Campbell, Dimpho Radebe, Emily Moore

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2022
Typearticle
Languageen
FieldEngineering
TopicEngineering Education and Curriculum Development
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Toronto
KeywordsCognitive reframingResistance (ecology)Leadership studiesEducational leadershipEngineering ethicsLeadership developmentNeuroleadershipShared leadershipServant leadershipEmpirical researchSociologyLeadership styleTransactional leadershipManagementPublic relationsPolitical scienceEngineeringPsychologyEpistemologyPedagogySocial psychology

Abstract

fetched live from OpenAlex

Early studies of engineering leadership in North America suggest widespread resistance to leadership among engineering students and professionals. We explore two integrally linked strategies for overcoming this resistance—one conceptual and one empirical. First, we draw on Giroux’s theory of resistance to reframe the assumption that engineers who have questions about leadership are opposing the notion of engineering as a leadership profession. Second, we investigate the notion of leadership affinity by analyzing 617 open-ended survey responses to the following question: “what inspires you about an engineering profession that embraces leadership?” We conclude with a theoretically informed discussion about the potential impact of leadership affinity on engineers’ professional development and social impact.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.239
Teacher spread0.219 · 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.

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
Published2022
Admission routes3
Has abstractyes

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