Investigation of Pre-Service Teachers’ Tolerance Tendencies and Democratic Tendencies
Bibliographic record
Abstract
The current study aims to investigate whether pre-service teachers’ tolerance tendencies and democratic tendencies vary significantly depending on gender and mother and father’s education level and the relationship between their tolerance tendencies and democratic tendencies. A total of 417 second-year students from the departments of Turkish teaching, social studies teaching, elementary school teacher training, pre-school teacher training, science teaching, elementary school math teaching, arts, music, psychological counselling and guidance, English teaching and German teaching participated in the current study. In the analysis of the collected data, frequencies, percentages, Mann Whitney U test, Kruskall Wallis test and correlation analysis were used. As a result of the analyses, the pre-service teachers’ tolerance tendencies were found to be very high. The female pre-service teachers’ tolerance tendencies were found to be higher than those of the male pre-service teachers. The pre-service teachers’ tolerance tendencies were found to be not varying significantly depending on mother and father’s education level. The pre-service teachers’ democratic tendencies were found to be higher than the medium level. The female pre-service teachers’ democratic tendencies were found to be higher than those of the male pre-service teachers. The pre-service teachers’ democratic tendencies were found to be not varying significantly depending on mother and father’s education level. A positive, medium and significant correlation was found between the pre-service teachers’ tolerance tendencies and democratic tendencies.
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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 | 0.006 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".