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Record W2896796197 · doi:10.5430/wje.v8n5p31

A Metasynthesis Study Related to Exhaustion Concept of Teachers in Turkey

2018· article· en· W2896796197 on OpenAlexvenueno aff
Ebru Araç Ilgar

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PsychologyEmotional exhaustionResearch designQualitative researchMultimethodologyMeta-analysisEducational researchApplied psychologyPedagogyMathematics educationBurnoutSocial scienceClinical psychologySociologyMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.160
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.049
GPT teacher head0.342
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2018
Admission routes1
Has abstractyes

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