Teacher attitudes in shaping the culture of South African public schools
Bibliographic record
Abstract
In this paper we investigated the attitudes of teachers in shaping the culture of schools. In the 21st century, schools face new challenges within increasingly diversified environments. Emphasis is now placed on the need for school leaders and teachers to continually and explicitly create, understand, and nurture school culture so that schools become adept at innovating within the pervasive context of educational diversity and renewal. We examined the culture of two schools in order to gain a better understanding of teacher attitudes of each school's cultural setting. Data were sourced from focus group interviews and observations. The major finding of this research revealed that the culture of schools not only have a significant impact on the conditions of both teaching and learning, but also on the extent to which values, beliefs and norms of connectedness, belonging, and identity are fostered. There is thus a critical need for principals and teachers to focus on the cultural environment prevalent within their schools.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".