“Not try to save them or ask them to breathe through their oppression”: Educator perceptions and the need for a human-centered, liberatory approach to social and emotional learning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Introduction Social and emotional learning (SEL) has been identified as one approach to promote positive mental health outcomes while alleviating the stressors of systemic racism and a global pandemic. As the United States turns to SEL as a remedy for mental health challenges and the current civil unrest, it becomes increasingly relevant to understand what SEL means to those who use it the most to strengthen the implementation of current programs as well as to inform the development of new programs to fill existing gaps. Methods This abductive qualitative study expands prior research by exploring how in-service educators define SEL ( N = 427). Results Our findings highlight that educators perceive SEL as more expansive than current competency-based models. Educators describe SEL as a praxis that can be responsive to student and community needs, facilitate healing, and center humanity along with racial and social justice. Discussion We discuss implications that highlight the potential risks and harm that can be perpetuated by the current practice of SEL and, like the educators in our study, advocate for dismantling white supremacy structures in education through the co-creation of a humanizing SEL approach.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it