Work in Transition: Cultural Capital and Highly Skilled Migrants' Passages into the Labour Market
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
Despite the fact that many countries target highly skilled migrants for recruitment in the global labour market, few of those migrants are able to take full advantage of their educational and professional qualifications in their new homes. Work in Transition examines this paradox, using extended narrative interviews that focus on the role that cultural capital plays in the labour market.Comparing the migrant experience in Germany, Canada, and Turkey, Work in Transition shows how migrants develop their cultural capital in order to enter the workforce, as well as how failure to leverage that capital can lead to permanent exclusion from professional positions. Exposing the mechanisms that drive inclusion and exclusion for migrants from a transatlantic comparative perspective, this book provides a unique analytical approach to an increasingly important global issue
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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 | 0.001 | 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 | 0.000 | 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) | 0.002 | 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