Application of Employability Skills and Contextual Performance Level of Employees in Government Agencies
Bibliographic record
Abstract
The widespread practice of contractualization even in government institutions is a big challenge facing newly-hired employees in seeking a stable position. Researchers have argued that the quality of practice of employability skills could help employees have better job performance, provide them better working condition or status, and consequently meet the higher expectations of employers. The present study employs descriptive research design to explain the extent of application of employability skills and contextual performance. Based on The Conference Board of Canada’s Employability Skills 2000+ and Borman and Motowidlo’s Taxonomy of Contextual Performance, two sets of survey questionnaires were adopted to gather data from 220 respondents representing employers and employees from 25 government institutions. Data analysis showed that novice employees in public institutions applied their employability skills such as fundamental, personal management and teamwork skills to some extent. Moreover, results revealed that employees had satisfactory contextual performance. Thus, this may suggest that the application of employability skills and contextual behaviors should be enhanced to meet the increasing and complex challenges of their respective government agencies.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".