MétaCan
Menu
Back to cohort
Record W2932501233 · doi:10.1177/0891243219835737

Escalator or Step Stool? Gendered Labor and Token Processes in Tech Work

2019· article· en· W2932501233 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

VenueGender & Society · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsUniversity of Toronto
FundersDirectorate for Social, Behavioral and Economic Sciences
KeywordsMetaphorGender studiesSociologyRace (biology)Work (physics)White (mutation)Women of colorBlack womenCognitive reframingSocial psychologyPsychologyEngineering

Abstract

fetched live from OpenAlex

Gender scholars use the metaphor of the “glass escalator” to describe a tendency for men in women-dominated workplaces to be promoted into supervisory positions. More recently, scholars, including the metaphor’s original author, critique the glass escalator metaphor for not addressing the intersections of gender with other relevant identities or the ways that work has changed in the twenty-first century. I apply an intersectional lens to understand how gender and race shape women’s career paths in tech work, where twenty-first century changes to the organization of workplaces are common. I build on theories of raced and gendered labor and the glass escalator to make sense of women’s careers in a contemporary field dominated by men. I find some evidence that white women, but not women of color, experience something similar to a “glass escalator” where they are promoted into management, but those promotions are a smaller step up—more step stool than escalator. These promotions move women out of technical positions and towards business and management, releasing engineering teams from the pressure to fully incorporate women.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.289
Threshold uncertainty score0.650

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.086
GPT teacher head0.293
Teacher spread0.207 · 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