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Record W7140632331 · doi:10.3126/jore.v2i1.92051

Impact of Compensation Management on Employee Job Satisfaction

2025· article· W7140632331 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Research in Education · 2025
Typearticle
Language
FieldBusiness, Management and Accounting
TopicEmployee Welfare and Language Studies
Canadian institutionsWestern University
Fundersnot available
KeywordsJob satisfactionCompensation (psychology)Job securityJob designJob attitudeJob performancePersonnel psychologyRegression analysis

Abstract

fetched live from OpenAlex

The aim of this study is to find out the common compensation management practices and their effect on job satisfaction of employees. The required data were collected by means of a structured questionnaire which was distributed to the employees from ten commercial banks. The methods used for data analysis were Descriptive statistics, Kendall’s Tau correlation, and multiple regression analysis. The study finds the relation between the compensation variables: salary, promotion, bonus, recognition, and job security along with their impact on job satisfaction of employees in commercial banks of Nepal. The result shows that the compensation variables are positively related to job satisfaction of employees, meaning higher the compensation variables higher the job satisfaction. Among these factors, job security was seen as the most influential factor for job satisfaction of employees. The findings suggest that both financial and non-financial compensation elements are important for job satisfaction of Nepalese commercial banks. This study provides practical guidance for bank management and adds empirical evidence to the limited research on compensation management in Nepal’s banking sector, especially in Sudurpaschim Province of Nepal.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.048
GPT teacher head0.428
Teacher spread0.380 · 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