Post-Secondary Education in the Inner-City: Breaking barriers and building bridges in a divided city
Bibliographic record
Abstract
The Department of Urban and Inner-City Studies (UICS) is a department in the faculty of Arts at the University of Winnipeg in Manitoba, Canada. The Department is located outside of the main campus in one of Canada’s poorest neighbourhoods. UICS is intentionally located here to offer access to postsecondary education to people who might not otherwise attend university. Our department aims to encourage people who have come to believe that university is ‘not for them’. It also serves to bring students from other areas of the city into the neighbourhood to begin to dispel long held misconceptions about the North End. We continue to develop our critical, place-based model in the spirit of putting ‘reconciliation into action’. As described by Senator Murray Sinclair, the former Chair of the Truth and Reconciliation Commission of Canada, it is “‘up to society’ to step up and take the actions that are needed." (CBC 2017). At UICS, we are committed to ‘stepping up’ by creating opportunities for learning through honest dialogue, and challenging systemic divides in our community.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.045 | 0.024 |
| Scholarly communication | 0.017 | 0.009 |
| Open science | 0.004 | 0.025 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".