Engaging Children and Youth in Urban Planning and Environmental Design: A Guide to Youth Engagement in Montreal
Bibliographic record
Abstract
"In 2030, 60% of people living in cities will be under the age of 18. The present and the future of these cities must be planned for and with consultation of youth and children. However, there are many barriers to the consultation process that can exclude children and youth, especially from marginalized backgrounds. This supervised research report asks the question of why youth engagement is important and how we can make it more inclusive, meaningful and accessible to children and youth of all backgrounds. Exploring the research questions, the report reviews histories of engagement, the United Nations Convention on the Rights of the Child (CRC), examples of what engagement actually looks like, as well as insights from interviews with 6 Montreal-based organizations and initiatives. The findings emphasize innovative strategies to involve marginalized communities, such as targeted outreach and culturally sensitive methods. They also highlight the importance of establishing trust through sustained dialogue. This report concludes with insights and recommendations for future research and engagement. The hope for this research is to contribute to a more inclusive and equitable urban planning landscape that recognizes the vital role of youth and children."@eng
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.027 | 0.003 |
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".