The Chihuahua and the Space Princess writing in the margins: Antenarratives of two (older) women early career academics
Bibliographic record
Abstract
Abstract In asking “why is it so bloody hard for older women, with years of professional experience in industry and graduate degree holders, to create a career in the Academy?,” the authors co‐examine the challenges they experience in their careers and in their transition into academia. Framed within intersectionality scholarship, specifically anchor points, the authors' nonnormative positioning as older ciswomen, early career academics, who are attempting to find tenured positions, showcase their fluid living stories of sexism and ageism while trying to negotiate a career transition. Using a duoethnographic methodology, the authors share and then analyze their embodied, fragile antenarratives as they understand them at this point in time. In the process of writing differently, literally at the left and right margins of content and style, and in the analysis of these writings, they discover that they can begin to resist the gendered ageism from the margins and that they are no longer alone. They navigate a path of resistance, laboring against the norms that try to relegate two older women, early career academics' stories to silence, inviting others into their living story network.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.022 | 0.021 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".