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Record W2154706258 · doi:10.6007/ijarems/v3-i4/1113

Factors Impact Business Graduates Employability: Evidence from Academicians and Employers in Kuwait

2014· article· en· W2154706258 on OpenAlexaff
Abdullah AL Mutairi, Kamal Naser, Muna Saeid

Bibliographic record

VenueInternational Journal of Academic Research in Economics and Management Sciences · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education and Employability
Canadian institutionsAlgonquin College
Fundersnot available
KeywordsEmployabilityOrder (exchange)Soft skillsBusinessPsychologyMedical educationMarketingPublic relationsPedagogyPolitical scienceSocial psychologyMedicineFinance

Abstract

fetched live from OpenAlex

The objective of this study is to explore the importance that academicians and employers attach to factors impact business graduates employability in Kuwait. Four categories of employability factors were used in the current study covering graduates knowledge, soft skills, personal abilities and working with groups. A questionnaire that contained these factors was distributed to academicians as well as employers and they were asked to express the level of importance they assign to variables within each of these categories. The results of the analyses pointed to differences in the levels of importance academicians and employers attach to employability factors covered in the questionnaire, indicating that current programs offered by business schools in Kuwait are not responding to market needs. While employers attach high levels of importance to graduates knowledge, soft skills and personal abilities, academicians do not assign the same levels of importance to these factors. However, academicians and employers appeared to be consistent in the level of importance they attach to the working within group factor. Business schools are requested to develop their academic programs in order to respond to market's needs. This requires changes in the contents of these programs (input) together with teaching instruments in order to improve output and satisfy employers demand.

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)0.010
metaresearch head score (Gemma)0.001
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 score0.064
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0100.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.215
GPT teacher head0.486
Teacher spread0.271 · 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 teacher head, 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

Citations6
Published2014
Admission routes1
Has abstractyes

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