Factors Contributing Ecological Footprint Awareness of Turkish Pre-Service Teachers
Bibliographic record
Abstract
The purpose of this research is to determine ecological footprint awareness level of pre-service teachers who are majoring in three different programs of Teacher Education Department. The study also investigated whether there is a difference in ecological footprint awareness level based on gender, parents’ education, program of study, and longest lived place of residence. “Ecological Footprint Awareness Scale” which was developed by Coşkun & Sarıkaya (2014) was used as a data collection tool. The scale is a 5 point Likert type instrument which is composed of five dimensions related to food, shelter and mobility, water consumption, energy consumption, and waste management. One hundred and seventy pre-service teachers who are pursuing their third year in a College of Education of a medium size University located at northeast part of Turkey participated in the study. T-test and one-way analysis of variance (ANOVA) was used to analyze the data by utilizing SPSS statistical package. Results of the study revealed that the pre-service teachers’ awareness on ecological footprint is at a medium level; highest levels of awareness found in energy (X=4.15) and water consumption(X=3.83) dimensions. Least level of awareness detected in food dimension (X=3.04). Results of the study showed that pre-service teachers’ awareness level differed based on gender in food dimension of the scale (t=2.116, p
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".