Promoting emotional education : engaging children and young people with social, emotional and behavioural difficulties
Bibliographic record
Abstract
Introduction. Chapter 1. Emotional Education: Connecting With Students' Thoughts and Emotions. Carmel Cefai, University of Malta, and Paul Cooper, University of Leicester, UK. Part 1: Listening To Students' Voices. Chapter 2. The Perspectives of Young People With SEBD about Educational Provision. Frances Toynbee, Huntington School, York. Chapter 3. The Narratives of Secondary School Students with SEBD. Carmel Cefai and Paul Cooper. Chapter 4. The Perspectives of Ex-Students on Their Experiences at a School For SEBD. Damian Spiteri, College of Arts, Science and Technology, Malta. Chapter 5. The Perspectives of Students on Personal and Social Development in School. Mark G. Borg, University of Malta and Andrew Triganza Scott, PSD Teachers Association, Malta. Part 2: Mobilising Peer Support. Chapter 6. Peer Support Challenges School Bullying. Helen Cowie, University of Surrey, UK. Chapter 7. Classwide Peer Tutoring and Students With SEBD. Anastasia Karagiannakis and Ingrid Sladeczek, Both of Mcgill University, Canada. Chapter 8. Students with SEBD as Peer Helpers. Claire Beaumont, University of Laval, Quebec, Canada. Chapter 9. Circle Time and Socio-Emotional Competence in Children and Young People. Jenny Mosley, Quality Circle Time Consultancy. Part 3: Working With Students' Emotions. Chapter 10. Nurture Groups: An Evaluation of the Evidence. Paul Cooper. Chapter 11. Nurture Groups: Early Relationships and Mental Health. Marion Bennathan, Chair of the Nurture Group Network, UK. Chapter 12. Kangaroo Groups: An Adaptation of Nurture Groups. Caroline Couture, Universite Du Quebec A Trois-Rivieres, Canada. Chapter 13: Aggression Replacement Training: Decreasing Behaviour Problems by Increasing Emotional Competence. Knut Gundersen and Frode Svartdal, Both of Diakonhjemmet University College Rogaland, Norway. Chapter 14. From the Needs of Children to the Need for Children: Contemporary Values and their Implications for the Social and Emotional Well Being of Children. Paul Cooper and Carmel Cefai. The Contributors. Index
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.069 | 0.020 |
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".