Collaging the (Dis) <i>illusio</i> of Being International Early Career Women in Physical Education and Sport Sciences/Kinesiology
Bibliographic record
Abstract
The uncertainties surrounding the neoliberal labor market intersecting with many challenges lead us to try our best in understanding academia, specifically as women early career scholars in physical education and sport sciences/kinesiology. Unpacking academia, framed under the concept of illusio, takes time, but we feel we need to understand it fast to be able to remain in “the game.” Drawing on Bourdieusian, critical, and feminist frameworks, we aim to expand on why we are in academia and what shapes our experiences. In so doing, we hope to create spaces for dialogue and connection since we are not alone navigating these challenges, and further, we aim to contribute to social change. We use the concept of collage as a metaphor and claim (and complaint) to articulate our co-autoethnographic paper and as a research method to summarize reflexive processes for data generation from the singular to the plural.
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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 | 0.012 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.044 |
| Scholarly communication | 0.015 | 0.012 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".