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Record W4308803088 · doi:10.24908/pceea.vi.15842

Undergraduate Mentors’ Perspectives on Equity-Oriented STEM Outreach

2022· article· en· W4308803088 on OpenAlexafffundvenue
Callum Sutherland, Aida Mohammadi, Jeffrey Harris

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsYork University
FundersDirectorate for STEM EducationYork University
KeywordsMentorshipForegroundingOutreachEquity (law)Engineering ethicsSociologyPedagogyMedical educationPublic relationsPolitical scienceEngineeringMedicine

Abstract

fetched live from OpenAlex

This paper explores undergraduate mentors’ perspectives on, and participation in, “Bringing STEM to Life: Work Integrated Learning in Physics” (BSTL), a work-integrated, equity-oriented STEM outreach program administered by the kindergarten to industry (k2i) academy at York University’s Lassonde School of Engineering. To that end, this study brings Feminist Science and Technology Studies and critical pedagogy to bear on a three-phase methodological approach to generating and analyzing qualitative data pertaining to the mentorship component of BSTL. Preliminary findings suggest that (1) undergraduate mentors bring complex STEM motivations, shaped by intersecting marginalized identities, to bear on their mentorship duties; (2) mentors possess nuanced yet occasionally contradictory understandings of STEM, equity, and society; and (3) mentors’ experiences in the BSTL program are variable but positive. These findings suggest that outreach programs can expand their capacity to generate equitable outcomes by actively supporting the creation of STEM counterspaces, foregrounding equity training, and exposing mentors to critical theoretical perspectives on STEM, equity, and society.

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)0.000
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 score0.557
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.241
Teacher spread0.228 · 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

Citations5
Published2022
Admission routes3
Has abstractyes

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