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Record W2362906575

Analysis on Occupational Stress of Teachers in Charge of Classes and Teaching Graduating Classes in High School

2005· article· en· W2362906575 on OpenAlexaff
Yu-lan Jin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Work Dynamics
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsStressorPsychologyOccupational stressContentmentSchool teachersPromotion (chess)Coping (psychology)Job satisfactionMedical educationMathematics educationClinical psychologyMedicineSocial psychology
DOInot available

Abstract

fetched live from OpenAlex

Objective To explore the occupational stressors and their effects on mental health of teachers in charge of classes and teaching graduating classes in high school.Methods Occupational stressors and strains of 404 teachers from 3 high schools were investgated by generic job stress questionnaire recommended by Prof.Yu Shanfa,and the results analyzed.Results Results showed that the scores of intra conflict,job load,resp onsibility for people,job hazards,physical complain and daily life stress of teachers in charge of classes were higher than those teachers not in charge of any class,and their job control,supports from superiors and colleagues,job satisfaction and contentment of teachers in charge of classes were less than those of others.Teachers teaching graduating students felt poor environment,heavier job load,more responsibility for students,more role conflicts,less job monotonous and ease of mind,more physical complain and daily life stress,less opportunity of promotion and participation.The main modifiers of middle school teachers were behavior manners,coping strategy and self-esteem.Conclusions There are some differences in stressors between teachers in charge of classes and those teaching graduating classes,so different measures should be taken to protect these two kinds of teachers.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.025
GPT teacher head0.363
Teacher spread0.338 · 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
Published2005
Admission routes1
Has abstractyes

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