Penalized for Excellence: The Invisible Hand of Career-Track Stratification
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.
Bibliographic record
Abstract
Inequities persist in the engineering profession despite nearly four decades of diversity and inclusion efforts. In this paper, we propose an institutional mechanism to explain this persistence-career track stratification. When engineering educators and researchers frame engineers' careers as personal journeys, we implicitly characterize diverse promotion patterns as the product of individuals ' idiosyncratic interests, values, goals and competencies, leaving ourselves open to meritocratic explanations of career mobility. In contrast, when we account for systemic inequities in organizations and society by critically examining engineers' careers in the aggregate, it is possible to gain insights into the "hidden curriculum" 1 of professional advancement. In this paper, we take the latter approach, adopting a critical secondary analysis of data originally collected for a project on situated workplace learning. The key contribution of our analysis is to reframe the personal choice narrative of career advancement with a structural explanation of career stratification based on Jeannie Oakes' educational tracking research, and Audre Lord's powerful notion of "dominant fantasies." 2 To the extent that we treat engineers' career trajectories as differentially accessible opportunities rather than meritocratic products of individual competencies and preferences, we position ourselves well to understand and dismantle persistent inequities in the profession.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it