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Record W4397008144 · doi:10.31703/gesr.2024(ix-i).06

Effect of Teachers' Work-Related Burnout on Emotional Empathy at the Higher Education Level

2024· article· en· W4397008144 on OpenAlexaboutno aff
Iqra Jamshed, Almas Shoaib

Bibliographic record

VenueGlobal Educational Studies Review · 2024
Typearticle
Languageen
FieldNursing
TopicHealthcare Education and Workforce Issues
Canadian institutionsnot available
Fundersnot available
KeywordsBurnoutEmpathyPsychologyEmotional exhaustionEmotional laborWork (physics)Social psychologyApplied psychologyClinical psychologyEngineering

Abstract

fetched live from OpenAlex

Teachers’ burnout is a contributing factor to many teachers leaving the field of education early in their careers and emotional empathy is also related to teachers’ burnout. The factors of emotional empathy are interpersonal emotional empathy and intrapersonal emotional empathy. The objectives of the study were to examine teachers’ work-related burnout and emotional empathy at higher education levels and to investigate the effect of teachers’ work-related burnout on emotional empathy at higher education levels. The research design is based on causal-comparative. The population of the study includes teachers’ of social sciences and humanities from different public and private universities in Lahore. 100 teachers were selected by using a multi-stage sampling method. Maslach Burnout Inventory (MBI) and Toronto Empathy Questionnaire were used to conduct the study. The results show that teachers’ work-related burnout hurts teachers’ emotional empathy.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.439
Teacher spread0.382 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2024
Admission routes1
Has abstractyes

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