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Record W105103208

Women in Information Technology Initiatives in Canada: Towards Fact-based Evaluations

2004· article· en· W105103208 on OpenAlexfundaboutno aff
Wendy Cukier, Carole Chauncey

Bibliographic record

VenueJournal of the Association for Information Systems · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicGender and Technology in Education
Canadian institutionsnot available
FundersBritish Columbia Institute of TechnologyUniversity of OttawaUniversity of AlbertaUniversity of Calgary
KeywordsGovernment (linguistics)Order (exchange)Exploratory researchPrivate sectorExploratory analysisProgram evaluationManagement sciencePublic relationsComputer scienceKnowledge managementPolitical scienceBusinessEconomic growthEngineeringData sciencePublic administrationEconomicsSociologySocial science
DOInot available

Abstract

fetched live from OpenAlex

For more than a decade, government, the private sector, associations, universities and schools have initiated projects aimed at increasing the participation of women in information technology (IT).Despite these efforts, female enrolments in computer science, engineering and IT programs, have plateaued or even declined.While many initiatives report high levels of participant satisfaction, their other impacts are less clear.This exploratory study provides a meta-analysis of the program designs and evaluations of 70 such initiatives available in Canada.It assumes that programs need clearly defined assumptions, objectives and evaluation processes in order to be effective.It explores the assumptions that underlie the programs, the program elements and the forms of evaluation employed.The paper concludes that there is little systematic evaluation of these programs and that there is a need both to question some of their underlying assumptions and to develop more robust, multi-layered approaches to evaluation.

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)0.003
metaresearch head score (Gemma)0.003
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 score0.181
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.022
GPT teacher head0.303
Teacher spread0.281 · 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 designObservational
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

Citations2
Published2004
Admission routes2
Has abstractyes

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