Narrative Method of Practice Increases Curiosity and Exploration, Psychological Capital, and Personal Growth Leading to Career Clarity: A Retrospective Outcome Study
Bibliographic record
Abstract
The paradigm in career counselling is shifting from traditional matching assessments to narrative methods. Storytelling approaches, life design principles, and evidence-based methods of practice are integrating theory into practical tools that career professionals want to use and can easily learn. Evidence of effectiveness of such methods are key to their being implemented, and broad career management variables beyond employment status need to be identified. The retrospective outcome study of one such method reported here explored variables of hope, optimism, resilience, self-efficacy, collectively psychological capital, personal growth, and curiosity and exploration. Participants (N=68) were clients of a busy career management social enterprise. Analyses revealed statistically significant increases in all six career management variables, and identified key correlations with person-job fit, career clarity, and employment status. These results make a case for the continued adoption of narrative methods, and move this particular method into the realm of evidence-based practice.
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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 | 0.011 | 0.039 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".