Bibliographic record
Abstract
Foreword. Acknowledgments. Series Editor's Introduction Allan Luke Introduction: Youth, Mobility, and Identity Nadine Dolby and Fazal Rizvi Section 1: New Times, New Identities 1. The Corporate Curriculum and the Young Cyberflaneur as Citizen Jane Kenway and Elizabeth Bullen 2. Shoot the Elephant: Antagonistic Identities, Neo-Marxist Nostalgia, and the Remorselessly Vanishing Past Cameron McCarthy and Jennifer Logue 3. New Textual Worlds: Young People and Computer Games Catherine Beavis Section 2: Diasporic Youth: Rethinking Borders and Boundaries in the New Modernity 4. Consuming Difference: Stylish Hybridity, Diasporic Identity, and the Politics of Culture Michael Giardina 5. Diasporan Moves: African Canadian Youth and Identity Formation Jennifer Kelly 6. Popular Culture and Recognition: Narratives of Youth and Latinidad Angharad Valdivia 7. Mobile Students in Liquid Modernity: Negotiating the Politics of Transnational Identities Parlo Singh and Catherine Doherty Section 3: Youth and the Context: Transforming Us Where We Live 8. The Children of Liberalization: Youth Agency and Globalization in India Ritty Lukose 9. Youth Cultures of Consumption in Johannesburg Sarah Nuttall 10. Identities for Neoliberal Times: Constructing Enterprising Selves in an American Suburb Peter Demerath and Jill Lynch 11. Disciplining Generation M: The Paradox of Creating a Local National Identity in an Era of Global Flows Aaron Koh 12. Marginalization, Identity Formation, and Empowerment: Youth's Struggles for Self and Social Justice David Quijada
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.440 | 0.286 |
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".