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Record W2114586875 · doi:10.5539/ass.v6n1p80

The Study of Factors Contributing to Chef Turnover in Hotels in Klang Valley, Malaysia

2009· article· en· W2114586875 on OpenAlexvenueno aff
Rahman Abdullah, Mohd Azuan Mohd Alias, Harnizam Zahari, Noraida Abdul Karim, Siti Noraishah Abdullah, Hamdin Salleh, Mohd Fazli Musa

Bibliographic record

VenueAsian Social Science · 2009
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHospitality and Tourism Education
Canadian institutionsnot available
Fundersnot available
KeywordsTourismScope (computer science)BusinessTertiary sector of the economyMarketingProduct (mathematics)Service (business)Work (physics)Hotel industryHospitality industryTurnoverDeveloping countryEconomic growthEconomicsManagementGeographyEngineering

Abstract

fetched live from OpenAlex

Service plays a crucial role in the developed countries, and is a growing economic driver in developing countries. Since it offers more work opportunities than product based commodities, the service sector has been taken seriously for the past 30 years. The tourism industry in Malaysia is in the developing process and the service sector is the key driver towards its growth. The main focus of this study is to look at the hotel industry which is within the tourism industry that faces a major problem of employee turnover. In a much smaller scope; the focus would be on employee turnover in the kitchen department which had not been explored quite significantly. The study would attempt to discover aspects which actually perceived by the employees as important for them to retain employment in the kitchen.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.026
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.272
Teacher spread0.259 · 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

Citations19
Published2009
Admission routes1
Has abstractyes

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