Investigation of the Life Satisfaction Levels of Turkish EFL Teachers in Terms of Several Variables
Bibliographic record
Abstract
In the present study, the purpose was to investigate the life satisfaction levels of Turkish EFL (English as a foreign language) teachers in terms of several variables. The general survey method was used in the study. The life satisfaction scale, which was developed by Diener, Emmons, Larsen, and Griffin (1985), adapted into Turkish by Dağlı and Baysal (2016), was used to collect the data in the study. The data were collected through the internet from the teachers who taught English as a foreign language between January and March 2021. The software SPSS 24 version was used for the data analyses along with Spearman Correlation Coefficient, Kruskal-Wallis Test, and Mann Whitney U-Test. According to the results of the study, it was found that the life satisfaction levels increased in favor of female teachers in terms of the gender variable and in favor of married teachers according to the marital status variable; additionally, was found to increase in favor of those who received support from administrators and colleagues when it comes to the support received from administrators and colleagues. In the same way, life satisfaction levels were found to increase as age increased and in favor of those who considered themselves at upper-income level economically.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".