This is not what I signed up for―I’m a teacher, not a therapist: A teacher’s role in supporting student mental health
Bibliographic record
Abstract
As mental health becomes increasingly recognized as a responsibility of schools, there is greater onus on the teacher to take on an active role. Teachers generally want to help, but often feel inadequate and ill-prepared. Importantly, studies have shown that there is a bi-directional relationship between learning and mental health where good mental health enhances learning, and where underachievement negatively affects mental health. This study, a subset of a larger study, looks at the perspectives of students regarding the potential of teachers to affect their mental health. Twenty-four students in Grades 9 to 11 participated in this study. Journal entries and focus group data was compiled from three journal prompts, and six focus group questions. The findings showed that in terms of supporting their mental health, students wanted schools to be safe and caring places, and teachers to be nurturing, authentic, and responsive teachers―not therapists. This finding is particularly important when considering many teachers lack self-efficacy in being able to positively affect the mental health of their students. By embracing the opportunity to support students’ mental health in their classrooms, teachers have the potential to positively impact students’ mental health and well-being, both during their school years, and beyond.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.026 | 0.013 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.004 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".