School Climate of Educational Institutions: Design and Validation of a Diagnostic Scale
Bibliographic record
Abstract
School climate is recognized as a relevant factor for the improvement of educative processes, favoring the administrative processes and optimum school performance. The present article is the result of a quantitative research model which had the objective of psychometrically designing and validating a scale to diagnose the organizational climate of educational institutions. This study had the participation of 549 teachers and directors from 42 primary and secondary educational establishments of Chile. Diverse procedures were applied for the validation of content and psychometric validation in the various stages of the investigation, obtaining an instrument composed by seven factors and made up of conceptually and statistically consistent items. The complete scale and its sub-scales show adequate reliability, and likewise an appropriate validity, constituting it an instrument of wide use for supporting the process of education administration, and to promote coexistence climates of appreciation and respect among the educational participants. The complete scale and its subscales permits the understanding that the organizational climate of the educational center is not reduced to the teacher-student relationship, but rather contemplates the dynamic relationships between diverse players, establishing the importance of the joint action between teachers, directives, students, and parents, as well as revealing the importance of some structural organization variables which influence the daily perception of school climate.
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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 | 0.017 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".