CONCEPTIONS OF SUSTAINABLE SCHOOLS AND ENVIRONMENTAL EDUCATION AND SUSTAINABILITY ACTIONS IN A PUBLIC SCHOOL IN ITAPEMA MUNICIPALITY
Bibliographic record
Abstract
The present research aims to verify how managers and teachers observe the Environmental Education and Sustainability actions in a Public School of Itapema. The research involved managers and teachers who were submitted to a questionnaire on issues related to sustainability and environmental practices carried out at the school. For the formulation of the questionnaires, were considered: the Sustainable Schools Manual (BRAZIL, 2013), the National Sustainable Schools Program (BRAZIL, 2014), the Curriculum Ambientalization Guide in Higher Education: Practice theory and theorizing practice (FIGUEIREDO; GUERRA; ANDRADE, 2017), and the Master's Dissertation of Vieira (2017). This research was based on Sustainable Educational Spaces, the National Curricular Guidelines for Environmental Education - DCNEA (BRAZIL, 2012); the Sustainable Schools Manual (BRAZIL, 2013); the National Sustainable Schools Program (BRAZIL, 2014); already, for the analysis of the results of the questionnaires, the article by Sauvé (2005) on currents in environmental education was used. With regard to the data obtained, it can be observed that the subjects of the researched school present different discourses about what a sustainable school would be, as well as, at times, their responses converge and diverge among themselves. We conclude by believing that this research can contribute to at least the subjects of the research can reflect on their attitudes and practices towards Environmental Education and Sustainability for the transformation of the school unit into a Sustainable Educational Space (BRAZIL, 2012).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".