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Record W2316413035 · doi:10.7202/1003580ar

JANE MARGOLIS, Rachel Estrella, Joanna Goode, Jennifer Jellison Holme, & Kimberly Nao. Stuck in the Shallow End: Education, race and computing. Cambridge MA: MIT Press (2008). 216 pp. C$ 18.24 (hard cover) (ISBN 13 978-0-262-13504-7)

2010· article· en· W2316413035 on OpenAlexaffvenueabout
Dorian Stoilescu

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDigital Games and Media
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRace (biology)HumanitiesCover (algebra)Art historySociologyMedia studiesArtEngineeringGender studiesMechanical engineering

Abstract

fetched live from OpenAlex

JANE MARGOLIS, Rachel Estrella, Joanna Goode, Jennifer Jellison Holme, & Kimberly Nao. Stuck in the Shallow End: Education, race and computing. Cambridge MA: MIT Press (2008). 216 pp. C$ 18.24 (hard cover) (ISBN 13 978-0-262-13504-7). Un article de la revue McGill Journal of Education / Revue des sciences de l'éducation de McGill (Volume 45, numéro 3, fall 2010, p. 331-615) diffusée par la plateforme Érudit.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.167
Threshold uncertainty score0.559

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.007
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.1670.102

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 head0.149
GPT teacher head0.382
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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
Published2010
Admission routes3
Has abstractyes

Explore more

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