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Record W4281298284 · doi:10.5539/ijps.v14n2p40

The Mediating Role of the Meaning of Work in the Relationship between Organizational Constraints and Psychological Well-Being at Work

2022· article· en· W4281298284 on OpenAlexvenueno aff
Samuel Nyock Ilouga, Aude Carine Moussa Mouloungui

Bibliographic record

VenueInternational Journal of Psychological Studies · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Management
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)WorkloadPsychologyWork (physics)Multilevel modelPerspective (graphical)Social psychologyWork engagementManagementPsychotherapistComputer scienceMathematicsStatistics

Abstract

fetched live from OpenAlex

This study examines the mediating role of the meaning of work in the relationship between organizational constraints and well-being at work. A selection of two inductors of the work situation was done in the framework of this study because of their explanatory power related to well - being at worknamely: workload and hierarchical support. Our hypothesis postulates that the meaning of work combines with the characteristics of the work situation to determine well-being at work (BET). In other words, we believe that the meaning of work mediates the effects of organizational inductors on well-being at work. In this perspective, 581 teachers from primary and secondary schools all sectors included (public, private, denominational, etc.) of the city of Yaounde (Cameroon) and aged between 21 and 60 years (M = 35.3, σ = 7.9) were interviewed using a self-report questionnaire. Multiple regression analyses following the procedure of Baron and Kenny (1986) confirm the mediating role of the meaning of work in the relationship between workload, hierarchical support and well-being at work.

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)0.010
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 score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.001
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 head0.171
GPT teacher head0.485
Teacher spread0.314 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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