Youth employability training: two experiments
Bibliographic record
Abstract
Purpose This paper aims to assess the effectiveness of verbal self‐guidance (VSG) and self‐management on youth employability. It seeks to access the joint effectiveness of these interventions, grounded in social cognitive and goal setting theories, for youth job seekers. Design/methodology/approach The studies used experimental designs involving participants enrolled in an undergraduate business cooperative degree program. Survey data assessing self‐efficacy and anxiety were collected pre and post‐training. Interview performance was also assessed in each study. Findings In study 1, it was found that students trained in self‐management and verbal self‐guidance (SMVSG) improved interview performance and reduced anxiety. In study 2, it was found that self‐efficacy and job search effort were higher in the SMVSG group relative to VSG alone. Research limitations/implications For study 1, the only measure of employment was a mock interview. For study 2, a limitation was that approximately 25 per cent of participants failed to either complete the post‐training survey or attend the interview. Practical implications Overall the studies describe a relatively simple and low cost training intervention, and associated performance measures, that can continue to be used by practitioners and scholars with future groups of youth job seekers. Originality/value The paper shows that these studies further support the effectiveness of VSG‐based interventions for employability. The paper also shows the value of augmenting VSG training with self‐management training in the context of youth employability. Furthermore, this research also considered anxiety, a key variable in successful employment that has often been omitted in the literature.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
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".