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Record W3204603062 · doi:10.1108/ijoa-02-2021-2608

Do values reflect what is important? Exploring the nexus between work values, work engagement and job burnout

2021· article· en· W3204603062 on OpenAlexaff
Rinki Dahiya, Juhi Raghuvanshi

Bibliographic record

VenueInternational journal of organizational analysis · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsUniversity of FrederictonUniversity of New Brunswick
Fundersnot available
KeywordsWork engagementBurnoutDisengagement theoryPsychologyWork (physics)Job securitySocial psychologyOriginalityNexus (standard)Value (mathematics)Applied psychologyMedicineCreativityClinical psychologyComputer science

Abstract

fetched live from OpenAlex

Purpose Work values are a representation of people’s priorities as they reflect what is pertinent for them and what they want to accomplish. In light of this, the purpose of this study is to understand the priorities given to work values (extrinsic and intrinsic) by employees and also to explore whether these work values vary with the levels of work engagement and job burnout. Design/methodology/approach The study was based on the survey responses of 386 officers working in Indian manufacturing organisations engaged in different areas. Findings The findings reveal that security officers give much priority to extrinsic work values than intrinsic work values (IWVs). Moreover, IWVs vary with different levels of work engagement along with job burnout. The security officers belonging to the engaged group differ significantly with those belonging to the job burnout group in terms of IWVs. Moreover, work values also have a negative correlation with job burnout and a positive correlation with work engagement. Originality/value This study explores the variation in work values of security officers working in Indian manufacturing organisations with changes in levels of job burnout and work engagement, which is a novel contribution in the field. The findings also advocate that it is crucial for human resource managers, supervisors and key people in organisations to find out employees showing early signs of job burnout (exhaustion or disengagement) or early stages of strain and frustration as the priorities of work values of the employees are affected by these parameters. Such identified employees should be provided with required managerial support and necessary work resources immediately.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient 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 score0.020
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.038
GPT teacher head0.281
Teacher spread0.244 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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