Factors Affecting Work Readiness of Economics Graduates in Digital Age: An Empirical Study in Vietnam
Why this work is in the frame
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Bibliographic record
Abstract
The article aims at identifying factors affecting the work readiness of economics graduates in the digital age, focusing on the perspective of employees. To realize this objective, based on literature review, a research model has been proposed with 6 hypotheses and tested via the use of Stata 17 and the participation of 450 economics graduates. The research findings indicate 4 factors with significant impacts on the work readiness of economics students, including Digital literacy, Identity Capital, Psychological Capital and Human capital, of which Digital literacy has the strongest impact and Human capital has the lowest impact; the other 2 factors, Social capital and Cultural capital, do not significantly impact the work readiness of economics students in the current digital context. Based on these findings, some implications and proposals have been made to students, educational institutions, businesses as well as policy makers so as to improve the work readiness of 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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