Embracing the “third space” in higher education
Bibliographic record
Abstract
This paper presents a case for integrating students as partners (SaP) within the curriculum of higher education (HE), particularly through the lens of “third space” learning. Drawing on our experiences as a collaborative of educators in Canada and the United Kingdom, we explore the liberatory potential of play, partnership, and co-creation in HE. Through the Becoming an Educationist (Becoming) module, we demonstrate how SaP can empower students—especially non-traditional students in UK post-1992 universities, that is, UK institutions with a strong focus on widening participation, applied learning, and “social mobility” or transformative learning—to find their voice in academia. We argue for embedding SaP within the curriculum to foster a sustainable ecology of collaborative practice for social justice, challenging traditional divisive structures in education.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.045 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.002 | 0.045 |
| Research integrity | 0.004 | 0.007 |
| 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".