A study of social-emotional climate within secondary school music classroom settings
Bibliographic record
Abstract
In the context of today's diverse society, issues of social justice and social climate have strong influence on educational policy and practice. In this societal and educational context, social and emotional climate in the school and classroom has moved to centre stage. Cameron and Carlisle (2004) view social climate as a formative phenomenon that includes macro foci and the micro focus. They argue social-emotional climate allows for individual perspective to develop within the context of macro and micro interactions between members of a group and the perceptions members hold of those interactions. The social-emotional climate of three southern Ontario secondary school music programs offering alternative learning experiences to large ensemble performance was studied using multiple research methodologies: semi-structured dyadic interviews with school principals and music teachers, formal and informal student focus group interviews, and phenomenological description. I examined the formative and experiential dimensions of the school music programs studied. The data indicated while the school principal plays a pivotal formative role within the school, it is the teacher who has direct and ongoing contact with students. The teacher's pedagogical choices are simultaneously influenced by and act as a formative force upon the perceptions of the school, the music program, and the relationship between the principal and music teacher. The music teacher is a significant formative influence upon students' experience. The qualitative student data indicated students match their behaviour to the formative structure of each music program. The data indicated the formative structure of the three music programs is designed with students' needs and connections to learning in mind. The quantitative student data indicated a trio of significant correlations between: the importance of what students learn in class and the relevance to their lives outside of school, the importance of what students learn in class and how creative students feel when engaged in music class, and how creative students feel when engaged in music class and the relevance to their lives outside of school. In conclusion, the study's findings indicate the pedagogical and behavioural choices teachers make within formative structures significantly influence and affect students' experience of music in secondary school.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.008 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".