Leading schools impacted by poverty: case studies from three Winnipeg schools
Bibliographic record
Abstract
This study examined the perceptions of three inner city principals on how poverty impacts the school experience and success for children attending high poverty schools in the Winnipeg School Division. This study focused on how three principals defined and understood poverty; how they created a vision for their school as well as exploring the sustainability of their work. The study examined and explored the frameworks and strategies that each principal worked from in an effort to address the impact of poverty on their schools. In doing this, the thesis attempts to tell the stories of three school principals who spent their entire careers working in the inner city district of the Winnipeg School Division. The schools examined in this study exist within a current reality in stark contrast to the one sought in the Mission and Vision for all students by Manitoba Education. The study found that there is a need for greater professional development for principals on the issue of complex poverty and how it impacts schooling. Although participants outlined a great deal of programming that is already in place to support children attending high poverty schools, all felt that much more can, and should, be done to improve conditions for children impacted by poverty. Findings suggest that policy and practice at the school, district, and provincial levels need to be examined and, where necessary, changed to address the needs of students and families impacted by poverty.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.030 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".