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Record W2516997759 · doi:10.5539/ass.v12n9p193

Workplace Spirituality among Malaysian Community Service Employees in the Public Sector

2016· article· en· W2516997759 on OpenAlexvenueno aff
Aminah Ahmad, Zoharah Omar

Bibliographic record

VenueAsian Social Science · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicWorkplace Spirituality and Leadership
Canadian institutionsnot available
Fundersnot available
KeywordsSpiritualityWorkplace spiritualityContext (archaeology)Public servicePublic sectorPublic relationsService (business)Sense of communityPsychologyTertiary sector of the economyPrivate sectorWork (physics)Social psychologySociologyBusinessMarketingPolitical scienceMedicineEngineering

Abstract

fetched live from OpenAlex

<p class="a"><span lang="EN-US">Despite the number of individuals who engage in pursuits for spirituality in their daily lives, there is still lack of studies examining spirituality in the workplace especially in the public sector. This study explored the experience of spirituality at the workplace among community service employees in a public sector organization. The dimensions of spirituality studied include meaningful work, sense of community and alignment of individual values with organizational values. Survey data from 180 community service employees revealed that overall the employees experienced a reasonably high level of spirituality, and employees experienced meaningfulness of work more as compared to the sense of community, and alignment of values. The results imply that the community service organization studied serves as a favorable environment that fosters the experience of spirituality among its employees. Though limited by the monosectoral nature of this investigation and the Eastern context, future researchers are encouraged to compare employees’ experiences in workplace spirituality in both the public and private service sectors as well as in both the Eastern and Western contexts. </span></p>

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)0.014
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.473
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0050.006
Scholarly communication0.0010.002
Open science0.0030.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.085
GPT teacher head0.335
Teacher spread0.249 · 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; both teacher heads agree on what is shown here.

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

Citations15
Published2016
Admission routes1
Has abstractyes

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