Career Development Practices: What Theories and Models Have to Offer
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
Career theory serves as a crucial foundation for practice, yet its relevance is sometimes questioned due to a perceived gap between theory and its practical application. We contend that the practical utility of theory should be a central criterion in evaluating contemporary career theories and models. This study aimed to bridge the gap between theory and practice by analyzing the practical applications of 43 career theories and models featured in Career Theories and Models at Work: Ideas for Practice (Arthur et al., 2019). Through thematic analysis, eight foundational themes emerged that support theory-driven practice. We argue that, regardless of their theoretical orientation, career practitioners can benefit from understanding and applying these themes. The results are discussed with a focus on making career theories and models more accessible for integration into practice. Practice points developed by the contributing chapter authors are provided, illustrating how specific theories and models informed the eight themes. Suggestions are offered for aligning the themes with professional standards and guidelines, and for improving learning and supervision.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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