The Role of the Principal in Supporting Learning for Students in High-Poverty Elementary Schools
Bibliographic record
Abstract
Students enter the school systems with a variety of needs and experiences, each unique to themselves. Unfortunately, many students and their families experience the effects of poverty, and these circumstances shape those school students’ unique needs. As the current times become more challenging, principals and teachers are faced with great demands to meet the needs of the students they serve. High-poverty schools need the expertise of successful principals who are aware of and acknowledge the impact of poverty on student learning; and are able to assist teachers to not only understand the impact poverty has on students’ social and academic learning but to provide supports to help students become successful learners. This hybrid thesis model used an exploratory case study and elements of an Organization Improvement Plan to examine how successful principals can assist teachers in high-poverty elementary schools understand the impact of poverty on student learning? And, how can they assist teachers in enhancing their teaching practices to improve student learning? Semi-structured interviews were conducted with two elementary school principals and 16 elementary school teachers in one Ontario School Board. The research findings provided unique insights into the work being done by successful principals and teachers striving to move high-poverty schools to high-performing schools. The analysis of the findings led to future recommendations being provided to the school board for their utilization in school improvement planning in service to students, teachers, and principals.\nKeywords: poverty, essential needs, lived experiences, relationships, successful principals, teachers, professional development
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.017 | 0.009 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| 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".