Understanding Careers Around the Globe
Bibliographic record
Abstract
This fascinating book comprises case studies of careers from 24 countries across the globe, highlighting culture-specific career issues, and encouraging reflection on one's own career. Interwoven with current theoretical and empirical insights from career studies, it emphasises the importance of our respective contextual settings. Reflecting socio-political changes around the globe, the book discusses a range of factors that can influence career success, including personal characteristics, stability and change, boundaries and borders, and gender. Chapters examine key themes such as career reinvention, professional resilience in times of financial crisis, support for immigrants in transitioning to local labour markets, and the effect of Brexit on career motivations, across countries including Argentina, Canada, India, Japan, Nigeria, and Switzerland. Throughout the book, contributors consider three defined perspectives on careers - ontic, spatial, and temporal - to identify the fundamental aspects of careers around the world. Proposing new solutions to contemporary career issues, this book will be vital reading for students and teachers of human resource management, international business, organisational behaviour, economics and finance. It will also be beneficial for guidance counsellors, careers advisers and coaches, and HR professionals.
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How this classification was reachedexpand
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".