Boundaryless Careers: Bringing Back Boundaries
Bibliographic record
Abstract
Boundaryless career theories are increasingly prominent in career studies and management studies, and provide a new ‘status quo’ concerning modern careers. This paper contextualizes the boundaryless careers literature within management studies, and evaluates its contributions, including broadening concepts of career and focusing interorganizational career phenomena. It acknowledges the considerable stimulus given to career studies by this literature, but also offers a critique based on five issues: inaccurate labelling; loose definitions; overemphasis on personal agency; the normalization of boundaryless careers; and poor empirical support for the claimed dominance of boundaryless careers. Because these problems render the boundaryless career concept increasingly obsolete as a ‘leading edge’ construct in career studies, we offer new directions for theory and research. In particular we re-examine the role of career boundaries, and suggest the development of new, boundary-focused careers scholarship based on boundary theory, to facilitate studies of the processes whereby career boundaries are created, and their effects in constraining, enabling and punctuating careers.
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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 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.035 |
| Scholarly communication | 0.011 | 0.020 |
| Open science | 0.002 | 0.017 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".