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Record W2617115702 · doi:10.18260/1-2--6348

A Theoretical Basis For Recruitment And Retention Interventions For Women In Engineering

2020· article· en· W2617115702 on OpenAlexaboutno aff
Stephanie Blaisdell, Catherine R. Cosgrove

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicCareer Development and Diversity
Canadian institutionsnot available
Fundersnot available
KeywordsBachelorPsychological interventionCommissionEngineering educationSession (web analytics)Representation (politics)Quarter (Canadian coin)PsychologyEngineeringGerontologyComputer scienceEngineering managementPolitical scienceMedicineHistoryLaw

Abstract

fetched live from OpenAlex

While women have dramatically increased their representation in many professions over the past t.hm decades, they continue to be underrepresented in engineenngl. LeBuffe, in her annual survey of engineering enrollments and degrees for the Engineering Workforee Commission of the American Association of Engineering Societies, found that roughly 16'ZO of all bachelor degnxs in engineering were awarded to women in 19932. In 1993, women received only 9% of the doctoral degrees in engineering3. In the first quarter of 1994 there were 127,000 women employed as engineers, which was roughly 7% of the engineering work

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.710
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.143
GPT teacher head0.328
Teacher spread0.184 · 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 designTheoretical or conceptual
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

Citations11
Published2020
Admission routes1
Has abstractyes

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