MétaCan
Menu
Back to cohort
Record W2211905153 · doi:10.5267/j.msl.2015.11.006

Improving employee productivity through work engagement: Evidence from higher education sector

2015· article· en· W2211905153 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueManagement Science Letters · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEmployee Performance and Management
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityEmployee engagementStructural equation modelingWork (physics)Work engagementSample (material)BusinessSurvey data collectionMarketingPublic relationsKnowledge managementPsychologyEconomicsPolitical scienceEngineeringComputer scienceEconomic growth

Abstract

fetched live from OpenAlex

Employee productivity is one of the important management topics that received significant research attentions from several scholars and considered as a primary mechanism to enhance organizational success. Knowing what are the key factors that influence productivity is vital to ensure long term performance. This study examines the effect of work engagement on employee productivity in higher education sector. To accomplish this purpose, the primary data using survey instrument were collected from a sample of 242 employees at public universities in northern Malaysia using an online survey method. The collected data was analyzed using SPSS and Structural equation modelling on AMOS. The results indicated that work engagement had significant positive effect on employee productivity. Moreover, this study provides an evidence that all of the dimensions of work engagement namely vigor, dedication, and absorption have significant positive effects on employee productivity.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.332
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0010.004
Open science0.0010.001
Research integrity0.0000.000
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 head0.087
GPT teacher head0.328
Teacher spread0.240 · 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