Student-to-staff partnership experience in a university-based humanitarian organization
Bibliographic record
Abstract
My journey of student-faculty partnership is one that I did not anticipate joining when I signed up for the International Students Overcoming War (ISOW) Scholarship Initiative. ISOW is part student-club, part humanitarian organization that provides students the opportunities to hone their leadership skills as they administer the operations of the scholarship program. The partnerships between students, staff, and Faculty create (experiential) learning for all that enhances personal and professional development in this community. Over the course of four years, with progressive leadership responsibilities ranging from Secretary to a full-time contract position, I have been able to experience partnership from the student and staff perspective. In this essay I share the key lessons I have learned about partnership as I moved through these roles and experienced the challenges of self-reflection, holding multiple identities, and moving on.
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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 | 0.009 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.027 | 0.013 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.003 | 0.023 |
| Research integrity | 0.004 | 0.009 |
| 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".