Challenges and opportunities facing Catholic schools in Western Canada: system leader perspectives
Bibliographic record
Abstract
Canadian school leaders must respond to widespread, twenty-first century social changes – post-pandemic polarisation, high rates of immigration, changing sexual mores, truth and reconciliation with Indigenous Peoples, and increasing demands for school choice. Based on exploratory interviews of Catholic system leaders in Alberta, Saskatchewan, and the Northwest Territories, this paper examines the particular challenges and opportunities facing these faith-based schools. Results uncover the pressures and polarisations faced by chief superintendents of schools, where differences among supporters makes leadership increasingly difficult. These system leaders engage both authenticity and vulnerability to find a path forward. Acting as bridge-builders, they try to respond effectively to these challenges and seek new possibilities through pragmatism, political mindedness, and their religious and educational ideals. This mindset might be duplicated by leaders globally in Catholic schools: priorities should focus on improved communication about the purpose of faith-based schooling, increased attention to governance and clearly defined roles, support for mission-driven teachers, and an emphasis on advocacy among constituents and the larger society.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.040 | 0.010 |
| Scholarly communication | 0.009 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".