Career Development among Entry-Level Employees: A Case Study on Employee’s in United Arab Emirates
Bibliographic record
Abstract
Career development is an integral part of personal and professional growth of the employees, so that, the alignment of the career objectives with the roles that the new employees are playing in the organization is evaluated and analyzed to identify their individual competencies, while, as per finding of the study where finding the following factors are most affecting on individual competencies Career management competencies (CMC) with T-statistics (14.545), Goal setting competencies (GSC) with (13.834), Skill development competencies (SDC) with (13.716), which that help in deriving its influence on their career growth across a course of time is determined, however, the newly hired employees in the organization can be provided with training related to their career goals, therefore, the development of a personal goals is very important to ensure that you excel your own performance and exceed your expectations in the organization. The results are derived by obtaining data from the participants that are the employees in different organizations in the UAE, the perspective of the new employees related to their career aspiration and the opportunity to attain them by working in their current organization is determined, moreover, The factors that the employees consider, during, selecting process is obtained in the recruitment period. It can be concluded that values, mindset, perception, vision of the employees affect their decision of selecting a company to guide their career objectives.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".