Matching University Graduates’ Competences with Employers’ Needs in Taiwan
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The dramatic expansion of the number of higher educational institutions in Taiwan has contributed a great deal to the growing unemployment rate of university graduates. Given the accumulated number of students who graduated in previous years and failed to find a job, the pressure of finding a job is growing each year. On the other hand, however, many employers lamented that they are struggling to find qualified job candidates. The major reason for this mismatch is that the traditional university instruction that most graduates receive is no longer adequate for the changing demands of the new market, and employers are also failed to notice that the definition of a good job perceived by students is very different from decades ago. To address this mismatch, it is important to understand what employers want in graduates and what students are seeking in a job. By administering questionnaires to both employers and university students, we endeavor to identify the component of a good job perceived by students, and skills demanded by employers for work accomplishment. Questionnaires were administered to 250 students and 250 employers, and many differences between the two parties were identified. Suggestions were given for students, universities, and employers to narrow the talent gap between employers and university graduates.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it