Bibliographic record
Abstract
Pedagogical partnership work continues to proliferate on college and university campuses around the world, and yet the language used in and about this work is still very much evolving. This exploratory study drew on surveys of student partners and program facilitators at institutions across contexts to learn about three related ways language is used: (a) to ensure respectful exchanges between student and faculty/staff partners within partnership programs, (b) to make pedagogical partnership work legible to those on campus not involved in the work, and (c) to communicate with prospective employers and others. Writing as a program facilitator and experienced student partner, we present findings from this study not to generalize or to compare institutional contexts and practices but rather to offer glimpses into the ways that student partners and program facilitators develop and use language to name partnership work that can inform ongoing explorations of this topic.
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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 | 0.026 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.065 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.006 | 0.013 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".