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Record W1662344010 · doi:10.5430/ijba.v6n4p48

The Effect of Identifying Training Needs on the Effectiveness of the Training Process and Improving the Individual and Organizational Performance: Applied Study in the Jordanian Health Sector

2015· article· en· W1662344010 on OpenAlexvenueno aff
Abdul Azez Badir Alnidawy

Bibliographic record

VenueInternational Journal of Business Administration · 2015
Typearticle
Languageen
FieldComputer Science
TopicOrganizational and Employee Performance
Canadian institutionsnot available
Fundersnot available
KeywordsProcess (computing)Training (meteorology)Sample (material)Set (abstract data type)Knowledge managementHuman resourcesWork (physics)Resource (disambiguation)Computer scienceBusinessProcess managementManagementEngineering

Abstract

fetched live from OpenAlex

Human resource is one of the organization important elements. Managers have big responsibilities to achieve organization desired objectives. Therefore, they have to use the training as a tool to develop and improve their employees. The organizations must work to identify employees and organization training needs accurately through the conversion of these requirements into training programs carried out inside or outside the organization which contributes to develop the current reality of the organization and preparing to the future needs. A questionnaire was designed to gathers data and it included (60) questions. The sample of the study are (100) employees. After the data was collected the proper statistical analysis was applied. The result showed that the identify on training need had big impact on the efficiency of the training programs and could improve the individual and organizational performance in the Jordanian health sector. This study also, recommended a set of conclusions and recommendations that achieve the purpose of this study.

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)0.005
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 score0.241
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.041
GPT teacher head0.283
Teacher spread0.242 · 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
Published2015
Admission routes1
Has abstractyes

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