Bibliographic record
Abstract
Social and emotional learning (SEL) is a crucial part of student wellness and academic achievement, but teachers’ own SEL is often overlooked. This qualitative study examines educators’ perceptions of their own university-level teacher preparation programs to better understand the ways in which teacher educators can support pre-service teachers’ well-being, preparedness, and longevity in the field. Findings reveal that teachers saw their own transformative SEL—a form of SEL committed to equity and social justice (Jagers et al., 2019)—as a key factor for their success, highlighting the importance of critical and holistic preparation that focuses on the social–emotional development of teachers themselves. Implications focus on practical ways transformative SEL can be infused into teacher preparation programs including redefining success beyond student academics alone, focusing on teacher well-being in a way that does not ignore systemic oppression and school-level barriers, preparing teachers for the realities of roadblocks and ethical dilemmas they may face, and examining syllabi and coursework for the development of transformative SEL competencies.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".