Youths growing up in the French banlieues: Partners that make the city
Bibliographic record
Abstract
How can cities become ‘livable’ for all urban residents? In this chapter, the authors explore the livable city as a city that is livable also for youths and also in marginalized urban areas by zooming in on the case of French youths growing up in the banlieues of Paris. Drawing on ethnographic research in Seine-Saint-Denis, a banlieue northeast of Paris, the authors explore the activities which banlieue youths undertake to realize quality of life in their city. The findings show that youths in the banlieues engage in ‘making their city’ in everyday practices and informal partnerships, even if they do not engage in ‘governing their city’ through formalized partnerships. Based on this study, the authors suggest that attention for informal practices that shape collective life in the city could inform a more inclusive perspective on urban decision making. Exploring the activities that youths take to ‘make the city’, this chapter teaches the reader not only that youths can be vital actors in partnerships for livable cities, but even more so how these partnerships can be effective and legitimate from the perspective of marginalized urban youths.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.008 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".