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Record W4386899490 · doi:10.26562/ijiris.2023.v0904.02

Fringe Benefits Effects on Employee Productivity in the Public Sector Tamilnadu Water Supply and Drainage Board Namakkal

2023· article· en· W4386899490 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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

VenueInternational Journal of Innovative Research in Information Security · 2023
Typearticle
Languageen
FieldDecision Sciences
TopicLeadership, Behavior, and Decision-Making Studies
Canadian institutionsnot available
Fundersnot available
KeywordsEmployee benefitsProductivityBusinessPensionRelocationWork (physics)Compensation of employeesEmployee moraleTurnoverMarketingPublic sectorHealth careJob securityCompensation (psychology)EconomicsFinanceEconomic growthManagement

Abstract

fetched live from OpenAlex

The research purpose is to determine the study of the fringe benefits important of employees. Fringe benefits are additions to compensation that companies give their employees. This research project is on Fringe Benefits and Employees productivity in public sector. This research work is generally about the Benefits and Employees productivity Public Sector. The project has undertook the general introduction into the research work led to the review of various literature that relates to the major variables involved in the research work especially employees productivity. The purpose of employee benefits is to increase the economic security of staff members, and in doing so, improve worker retention across the organization. As such, it is one component of reward management. In any case, employers use fringe benefits to help them recruit, motivate, and keep high-quality people. According to Mathis and John (2003), productivity is a measure of the quantity and quality of work done, considering the cost of the resources used. The more productive an organization, the better its competitive advantage, because the costs to produce its goods and services are lower. Employee benefits in Canada usually refer to employer sponsored life, disability, health, and dental plans. Employee benefits in the United States include relocation assistance; medical, prescription, vision and dental plans; health and dependent care flexible spending accounts; retirement benefit plans (pension, 401(k), 403(b). fringe benefits refers to the regular review of an employee’s job performance and overall contribution to a company. The objective is to know the effect of fringe benefits on employee motivation. The reveals that fringe benefits lead to improved employees’ performance. This results from increased productivity in the organization. The majorities of the employees are motivated of the organization through feedback and increased 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)0.025
metaresearch head score (Gemma)0.016
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0250.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.004
Science and technology studies0.0000.000
Scholarly communication0.0010.003
Open science0.0010.000
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 head0.221
GPT teacher head0.463
Teacher spread0.241 · 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