Escalator or Step Stool? Gendered Labor and Token Processes in Tech Work
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.022 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".