Editorial [International Journal of Emotional Education, 14(2)]
Bibliographic record
Abstract
The COVID-19 pandemic has helped to foreground mental health and wellbeing in education, underlining the need for a more caring education which addresses the social and emotional needs of students. It is becoming more evident than ever before, however, that educators cannot effectively support the social and wellbeing of students, unless their own social and emotional needs are addressed as well. As a result of the increasing evidence on the relationship between students’ and staff’s wellbeing, more attention is being given to the wellbeing of school staff as a prerequisite for quality education. In the first paper in this edition, Savage and Woloshyn (Canada) investigated the well-being, perceived stress, and use of coping strategies amongst 686 K-12 educators’ and school staff in Canada. They found that all educators regardless of their grade or position reported overall lower scores of wellbeing and higher levels of perceived stress when compared to the general population. Maladaptive coping strategies were related to poorer wellbeing and higher levels of stress.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.013 | 0.013 |
| Insufficient payload (model declined to judge) | 0.036 | 0.028 |
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".