University work-study programs transitioning from student employment opportunities to student-faculty partnerships
Bibliographic record
Abstract
Cook-Sather (2014) describes student-faculty pedagogical partnerships as a reciprocal collaboration where partners contribute equally, albeit in different ways, to the investigation, analysis, and implementation of curriculum or pedagogy.This partnership can vary in different contexts from curricular consultation to extra-curricular projects, and collaborative pedagogical research (Cook-Sather, 2014).The goal of student-faculty partnerships is to move away from the hierarchical nature of post-secondary institutions to engage students in a more collegial and holistic understanding of education and research (Healey et al., 2016).Students benefit from relationships outside of the classroom to support their personal and professional success (Tobolwsky et al., 2020).However, not surprisingly, power-sharing relationships between faculty and students can be difficult to navigate due to the institutional roles inherent in postsecondary institutions (Marquis et al., 2016;Seale et al., 2015).Student-faculty research partnerships are different from work-study programs, where post-secondary institutions across Ontario, Canada give undergraduate students an opportunity to get paid to work on campus while continuing their studies (University of Toronto, 2023).Pedagogical research projects offering undergraduate student work-study positions are generally considered to be employment positions where faculty and staff maintain a supervisory position over students.In 2020, our project transitioned undergraduate students from the Jackman Humanities Institute's Scholars-in-Residence (SiR) program at the University of Toronto (UofT) into work-study positions.This led to a convoluted journey where institutional guidelines led to ambiguities in expectations and roles for both the faculty and students.This student-faculty partnership is now entering its third year.As our work-study research student partner Erica de Souza is getting ready to graduate, our reflection on the journey from supervisor/student and employer/employee to research partners has been an insightful experience that we hope will inform other faculty, staff, and student relationships in post-secondary institutions. PROJECTOur pedagogical research project developed and implemented an undergraduate community-engaged learning (CEL) course, ANT241H, entitled Anthropology and Indigenous Peoples of Turtle Island (in Canada), under the direction of the Indigenous Action Group (IAG)
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.003 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.018 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".