The school‐to‐work transitions of second‐generation immigrant youth
Bibliographic record
Abstract
The children of immigrants obtain high levels of post-secondary attainment in Canada, but their ability to translate these educational credentials into good jobs varies among ethno-racial groups. To understand the social processes behind these unequal outcomes, we conducted in-depth interviews with 27 second-generation immigrant youth living in the province of Ontario. Motivated by the desire for intergenerational upward mobility and trusting in the widespread misrecognition of Canada as an education-based meritocracy, these young people pursued higher education as a means to gain entry into white-collar occupations. Despite their ambitions, the second-generation youth in this study did not have access to the 'career relevant' capital needed to mobilize their educational credentials in the white-collar labour market. And although they engaged in various forms of meta-work to help them acquire 'career-relevant' capital, the challenges they faced were not only the result of differential access to capital, but they also had to do with the way their capital was recognized in the labour market. The findings presented here emphasize the importance of considering how the intersection of multiple overlapping processes of social differentiation (i.e., immigrant status, class position, and ethno-racial background) shape second-generation youth's access to and recognition of 'career-relevant' capital in their school-to-work transitions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".