Engaging Student Mothers Creatively: Animated Stories of Navigating University, Inner City, and Home Worlds
Bibliographic record
Abstract
The article discusses a collaborative project undertaken in Saskatoon by Community Engagement and Outreach office at the University of Saskatchewan in partnership with undergraduate student mothers with lived experience of poverty. The results of the project were presented as an animated graphic narrative that seeks to make space for an under-represented student subpopulation, tracing strategies of survival among university, inner city and home worlds. The innovative animation format is intended to share with all citizens how community supports can be used to claim fairer health and education outcomes within system forces at play in society. This article discusses the project process, including the background stories of the students. The entire project, based at the University of Saskatchewan, Community Engagement and Outreach office at Station 20 West, in Saskatoon’s inner city, explores complex intersections of racialization, poverty and gender for the purpose of cultivating empathy and deeper understanding within the university to better support inner city students. amplifying community voices and emphasizing the social determinants of health in Saskatoon through animated stories.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".