A Holistic Approach to On-Reserve School Transformation: Pursuing Pedagogy, Leadership, Cultural Knowledge, and Mental Health as Paths of Change
Bibliographic record
Abstract
The aim of this manuscript is to present and discuss an attempt at transformative change in an on-reserve school in northern Saskatchewan. Myriad studies and government statistics have stated that on- reserve Indigenous students occupy the lowest levels of success in Canada as it relates to almost any recognized metric. In response to the ongoing inequity in education, a 3-year project was undertaken with potential national implications. In this project, a holistic approach was utilized which places an emphasis on leadership development, curriculum, teaching and learning, local Indigenous pedagogies, and mental health support. The confluence of approaches in this project have challenged standard approaches to school transformation by placing an emphasis on the local context and knowledge systems that already place the community in a position of strength. Data collection and project development was primarily focused on document analysis, classroom visits, meetings, and professional development with the faculty, planning sessions, instructional monitoring and student academic, cultural, and mental health assessments, and research projects. This manuscript offers wise practice considerations for diverse on- reserve schools through relationally collaborative interventions rooted in school psychology principles as key agents of change, resulting in: higher teacher retention; more comprehensive and effective lesson planning, implementation, and assessment; enhanced integration of Indigenous values within the classroom (e.g., PISIM); and improved teacher and student mental wellness in the classroom (e.g., teacher utilization of EFSS).
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.017 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.001 | 0.004 |
| 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".