Examination of the Concept of School Climate from the Perspective of Physical Education and Sports Teacher Candidates
Bibliographic record
Abstract
School climate, which is the sum of behaviors in a school, is also defined as the character of the school. A school’s climate has a significant impact on the quality of education, and on student success or failure. From this point of view, this study aims to examine the school climate from the perspectives of physical education and sports teacher candidates. To this end, the "School Climate Scale for University Students", developed by Ali R. Terzi, was applied to 303 physical education and sports teaching department students with three sub-factors. The data obtained were first subjected to a structure analysis and then to the reliability validity test, and the validity of the scale was determined. According to the type of variables, independent groups t-tests, one-way analysis of variance tests, post hoc tests, or effect size (Eta-square) tests were applied. While the answers given by the teacher candidates did not differ according to gender, a significant difference was found according to the grade they were studying in (in favor of first and fourth year students).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".