Running out of Care: Documenting and Contextualizing Ontario's Nursing Shortage
Bibliographic record
Abstract
This thesis explores Ontario’s current Registered Nurse shortage from the perspective of nurses. Qualitative research was used to gather 18 anonymous survey responses and 8 interviews that were interpreted using an Institutional Ethnography framework. Ongoing stressors identified by nurse respondents are discussed within an evidence-based institution-centered context that enhances understanding of the ongoing reports of increased Registered Nurse burnout. Nurses’ perspectives and lived experiences are foregrounded and their narratives are contextualized in processes drawn from secondary research. The main themes addressed are the current political backdrop and social-economic processes emanating from both institutional and government systems, as well as main stressors on nurses such as workload, patient acuity, short staffing, training and retention, new graduate experiences, managerial systems. Much of the research and respondents’ narratives highlight the institutional factors contributing to decreasing morale and mental health among nurses that has created perfuse burnout within this demographic, contributing to the current shortage in Ontario.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".