Constructing a Career: An Investigation of the Career Construction Model of Adaptation in Recent Graduates
Bibliographic record
Abstract
The transition from university to the workforce can be a daunting experience for many university graduates, due, at least in part, to an increasingly competitive, and often unstable labour market.University students are increasingly challenged to complete traditional classroom learning while also developing vocational identities and the skills needed to adapt to the 21 st century workforce.Career construction theory (Savickas, 1997(Savickas, , 2005) ) explains career development as a process of adaptation to career challenges, including key career transition skills.According to the model, successful career adaptation (adaptive results) is a function of relatively stable individual differences (adaptivity), psychosocial resources used to manage career-related challenges (adaptability resources), and the specific behaviours that people engage in to address occupational challenges (adaptive responses).Using a retrospective recall design, the current study tested some of the key theoretical assumptions of the career construction model of adaptation in the context of the school-to-work transition with a sample of 303 recent university graduates.The results showed that career adaptability resources mediated the relationship between adaptivity (proactive personality, cognitive flexibility) and adapting responses (proactive career behaviour, career construction behaviour).Career adaptability was also positively related to perceived career success and person-job fit perceptions; this positive relationship was partially mediated by proactive career behaviours.Overall, these findings support the career construction model of adaptation and contribute to a more comprehensive understanding of career construction theory and the school-to-work transition process.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".