Soluciones locales para un problema global. Los mejores ejemplos de lucha contra el extremismo en barrios empobrecidos y multiétnicos
Bibliographic record
Abstract
Studying the situation of two impoverished neighbourhoods \non the outskirts of Madrid and Paris provides an understanding of the link between isolation and extremism. Knowledge \nof the lives of these youths, through a qualitative comparative study, reveals the negative effects of disconnection from \nthe city, the poverty of social relations, ethnic segregation and \npolitical alienation. "e study also points out the benefits of \nsocialising among youths of diverse ethnic backgrounds and \nthe positive impact of civic engagement. "e paper, however, \ndoes not only confine itself to analysing the social problems, \nbut also seeks to identify the best ways to combat them. It does \nso through a critical assessment of the best examples of the \nfight against extremism and youth marginalisation in different European and Canadian cities and neighbourhoods, \ninterviewing mayors, police, civil servants, academics and \nmembers of civil society. "is contrast allows proposals to be \nbrought forth for preventing extremism, a global problem \nthat must be confronted with concrete solutions.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".