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Record W2136672881 · doi:10.5958/j.2319-5886.2.4.145

Levels of stress amongst the school teachers in a public school of rural Western Maharashtra

2013· article· en· W2136672881 on OpenAlexaff
Rahul Kunkulol, Rusina Karia, Prashant Patel, Abhinav David

Bibliographic record

VenueInternational Journal of Medical Research & Health Sciences · 2013
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsPontifical Institute of Mediaeval Studies
Fundersnot available
KeywordsStress (linguistics)SocioeconomicsSchool teachersRural areaMedicineMedical educationGeographyVeterinary medicinePsychologyMathematics educationSociologyPathology

Abstract

fetched live from OpenAlex

Teachers are among the professions reporting highest level of work-related stress, the study was undertaken to evaluate the levels of stress amongst school teachers in a public school of rural western Maharashtra Prospective survey based study was carried out amongst school teachers of rural western Maharashtra using Copenhagen Psychosocial Questionnaire (COPSOQ). The survey was carried out on 3 scheduled visits over a period of 2 months after the Institutional Ethical committee approval. Total 110 Primary and secondary school teachers, satisfying inclusion and exclusion criteria were randomly selected for the study. All the questions in the Copenhagen Psychosocial Questionnaire (COPSOQ) were graded according to 1 (Always-0), 2 (Sometimes-25), 3 (Often-50), 4 (Seldom-75) and 5 (Never-100). The scale value was calculated as the simple average. More the average score less the stress and vice versa Inability to understand the meaning and importance of work, improper clarity about the job, inability to cope with the problems were found to be the factors always contributing to stress 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 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)0.015
metaresearch head score (Gemma)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.987

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.247
GPT teacher head0.545
Teacher spread0.298 · 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 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

Citations2
Published2013
Admission routes1
Has abstractyes

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