A Metasynthesis Study Related to Exhaustion Concept of Teachers in Turkey
Bibliographic record
Abstract
The aim of the research is to determine teachers' exhaustion levels in Turkey, reasons, related factors, differentresearches the effects of subject areas have been carried out directly about issues in a systematic manner, gatheringthe studies that have been done over the last decade and making its meta-synthesis. Totally 35 studies consisting of26 theses and 9 articles determined by the purposeful sampling method between 1998 and 2018 were analyzed by aplanned meta-synthesis study in the qualitative research design. In order to determine the studies that will beincluded in the research; The National Teaching Center of the Higher Education Council, Google Academic searchengine, DergiPark, TUBITAK Ulakbim and ERIC databases were used. The sample group of studies used foranalysis constitutes exhaustion studies on teachers in public and private schools. According to research findings, thestudies carried out mainly concentrated on the four subscales. These are; the studies on the exhaustion anddemographic characteristics, the studies on the emotional states and the intelligence dimensions, the studies about theorganization and the states of belonging. In conclusion, in the context of the analyses made, it is considered that thisstudy will be useful in terms of future research direction and awareness of the exhaustion that teachers experience.
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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 | 0.024 | 0.049 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.018 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".