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Record W2159817807 · doi:10.2190/8ryv-9jwh-xqmb-qf41

Underrepresentation of Girls and Women in Computer Science: Classification of 1990s Research

2000· article· en· W2159817807 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Educational Computing Research · 2000
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Technology in Education
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGeneralizability theoryCategorizationMathematics educationComputer sciencePsychologyDevelopmental psychologyArtificial intelligence

Abstract

fetched live from OpenAlex

The proportions of Computer Science (CS) graduates who are women has been declining in the last fifteen years. At a time when the demand for computer programmers and systems analysts has been increasing, why are women becoming a smaller proportion of those enrolling in CS programs? This article presents a categorization by educational stages of the research into this topic, and an evaluation of the generalizability of findings to broader contexts. The categorization shows that the most extensive research on women in computing is done at the post-secondary stage, and uses students as non-randomly selected subjects. These studies are non-comprehensive, but where similar results are found in a number of studies, the findings are supported. The emphasis in research focuses on structural factors at the elementary stage, but by the post-secondary stage the emphasis is more likely to be on social psychological factors.

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.

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)0.021
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0210.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.232
GPT teacher head0.548
Teacher spread0.316 · 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