School Principals’ Work Intensification and Resilience: A Call for Structural Change
Bibliographic record
Abstract
Throughout the COVID-19 pandemic, principals have taken on increased responsibilities. Principals who are thriving are praised for their resilience while those who are struggling are inundated with calls to build their resilience. In this conceptual article, we problematize the overemphasis on individual responsibility that is implicit in pro-resilience narratives. We reviewed the interdisciplinary literature and used an inductive approach to examine resilience narratives across historical and disciplinary arcs, with specific attention given to the school leadership literature. We argue that, within the context of this pro-resilience movement, if attention is not given to the structural conditions of work intensification, the education system is setting K–12 principals up to experience adverse unintended consequences. These consequences can worsen existing mental health issues, such as occupational burnout, or exacerbate mental health stigma. We conclude by suggesting that structural changes could disrupt this individualization of responsibility and overreliance on the personal resiliency of school principals.
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 | 0.016 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.073 |
| Scholarly communication | 0.014 | 0.017 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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".