The Dynamics of Marginalized Youth
Bibliographic record
Abstract
This book studies young people who are Not in Education, Employment, or Training (NEET); a prime concern among policymakers. Moving past common interpretations of NEETs as a homogeneous group, it asks why some youth become NEET, whereas other do not. The authors analyse diverse school-to-work patterns of young NEETs in five typical countries and investigate the role of individual characteristics, countries' institutions and policies, and their complex interplay. Readers will come to understand youth marginalization as a process that may occur during the transition from school, vocational college, or university to work. By studying longitudinal analyses of processes and transitions, readers will gain the crucial insight that NEETs are not equally vulnerable, and that most NEETs will find their way back to the labour market. However, they will also see that in all countries, a group of long-term NEETs exists. These exceptionally vulnerable young people are sidelined from society and the labour market. The country cases and cross-national studies illustrate that policies intended to help long-term NEETs to find their way in society are very limited. The book provides useful theoretical and empirical insights for scholars interested in the school-to-work transition and marginalized youth. It also provides helpful insights in vulnerability to policymakers who aim to combat youth marginalization.
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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 | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".