The effect of soft skills, ethics, and value on the willingness of employers to continue recruiting UMT graduates
Bibliographic record
Abstract
This study aims to investigate the effect of soft skills and ethics and value on the employers’ willingness to continue recruiting Universiti Malaysia Terengganu (UMT) graduates, together with the moderating effect of knowledge on the relationship between soft skills and the employers’ willingness to continue recruiting UMT graduates. The study’s respondents comprised of 208 employers in Malaysia who responded through an online survey using Google Forms. The survey data was then analyzed using the Partial Least Squares Structural Equation Modelling (PLS-SEM), indicating that soft skills positively affected the employers’ willingness to continue recruiting UMT graduates. Nevertheless, ethics and value were found to be insignificant factors on the employers’ willingness to continue recruiting UMT graduates. It was also revealed that knowledge had the moderating effect on the relationship between soft skills and the employers’ willingness to continue recruiting UMT graduates. Therefore, universities were recommended to invest in soft skills and knowledge education to ensure that graduates met the employers’ professional recruitment standards in areas of expertise.
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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 | 0.005 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".