Positionality and Identity in Capstones:Renegotiating the self though teaching and learning
Bibliographic record
Abstract
Fostering inclusive and transformative capstone experiences—where students learn and faculty advance their scholarship—requires understanding the interplay of identities and social positions in the learning context. In higher education, diversity is generally viewed as a characteristic of the student body or a state to be pursued, camouflaging the fact that social identities are a set of power relationships that both structure social interactions—such as capstone experiences—and which are themselves restructured through social interaction. Capstones reproduce students in the image of what—or who—already exists, operating as a dialectic between student and faculty identities. Both student and faculty identities are subsumed by the perpetuation—even through critique—of the idea that today's university students have economic and social privilege similar to that of earlier generations of students. The capstone experience demands reaching beyond disciplinary knowledge to a place of reflexivity about one's relationship to that knowledge and the world; this includes awareness of positionality and identities.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.070 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".