Bibliographic record
Abstract
What does it mean to be young, to be economically disadvantaged, and to be subject to constant surveillance both from the formal agencies of the state and from the informal challenge of competing youth groups? What is life like for young people living on the fringe of global cities in late modernity, no longer at the center of city life, but pushed instead to new and insecure margins of the urban inner city? How are changing patterns of migration and work, along with shifting gender roles and expectations, impacting marginalized youth in the radically transformed urban city of the twenty-first century? In Lost Youth in the Global City, Jo-Anne Dillabough and Jacqueline Kennelly focus on young people who live at the margins of urban centers, the "edges" where low-income, immigrant, and other disenfranchised youth are increasingly finding and defining themselves. Taking the imperative of multi-sited ethnography and urban youth cultures as a starting point, this rich and layered book offers a detailed exploration of the ways in which these groups of young people, marked by economic disadvantage and ethnic and religious diversity, have sought to navigate a new urban terrain and, in so doing, have come to see themselves in new ways. By giving these young people shape and form – both looking across their experiences in different cities and attending to their particularities – Lost Youth in the Global City sets a productive and generative agenda for the field of critical youth studies.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.010 | 0.004 |
| Open science | 0.001 | 0.011 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".