Profiles, Knowledge, Skills, Abilities, and Other Characteristics A Case of Malaysian Government Retirees
Bibliographic record
Abstract
By the year 2020, Malaysia will be an ageing society ignited by the expected increase of senior citizens to 2.71 million. Thisgroup consists mainly of the government retirees, who have reached their mandatory retirement age of 56 years old. Theobjectives of this study are twofold. First, this paper examines the profiles of the Malaysian government retirees andsecond, to identify the current knowledge, skills, abilities, and other characteristics (KSAOs) they have. To elicit findings,a total of 1609 questionnaires were compiled and analyzed using SPSS. Findings indicate that most of the retirees haveacquired numerous KSAOs throughout their years of service, especially in the area that relates to their tasks andresponsibilities. However, once they have retired, these retirees are unable to harness their invaluable KSAOs for thecountry’s development. It is therefore of paramount importance for the government to develop a proper means for theseretirees to utilize their KSAOs. Recommendations emphasize several policy guidelines and activiti
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".