MétaCan
Menu
Back to cohort
Record W3034770092 · doi:10.5539/mas.v14n7p50

The Impact of Talent Management Strategies on the Employees’ Performance in the Ministry of Social Affairs and Labor MOSAL in the State of Kuwait

2020· article· en· W3034770092 on OpenAlexvenueno aff
Abdullah Sultan Saleh Al-Majroob, Mohammad Abdelkareem al Raggad, Abeer Fawaz Al-Abadi

Bibliographic record

VenueModern Applied Science · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicHuman Resource and Talent Management
Canadian institutionsnot available
Fundersnot available
KeywordsChristian ministryBusinessSample (material)Test (biology)PopulationWork (physics)State (computer science)Public relationsPolitical scienceEngineeringMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Talent management is of great importance to organizations in the public and private sectors, and this study aims to test the impact of talent management strategies on the employees’ performance in the Ministry of Social Affairs and Labor MOSAL in the State of Kuwait. The researchers conducted a study of a practical nature (Empirical) based on the discovery of cause and effect relationships (Causal & effect) between variables. The study population included employees of the Ministry of Social Affairs and Labor in Kuwait. The researchers decided to choose a convenience sample of 150 employees to distribute the questionnaire of the study. It is found that there is an impact of Talent Management Strategies on the employees’ performance in the Ministry of Social Affairs and Labor MOSAL in the State of Kuwait. The researchers recommended that employees in the Ministry of Social Affairs and Labor in Kuwait should be involved in the process of developing plans related to their work.

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)0.001
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 score0.747
Threshold uncertainty score0.262

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.019
GPT teacher head0.242
Teacher spread0.223 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueModern Applied ScienceSame topicHuman Resource and Talent ManagementFrench-language works237,207