Cities for Youth: A Pragmatic Approach to Engaging Youth Throughout the Urban Planning Process
Bibliographic record
Abstract
A wealth of perspectives exists in urban spaces; engagement opportunities in planning have the potential to collect theses perspectives and leverage them to shape urban futures. Recognizing the need for diverse and comprehensive community engagement opportunities in planning, this work looks towards how youth voices can be further integrated into the planning process. Youth represent active stakeholders in their communities, with a keen capacity to observe and recount their lived urban experienced. Existing literature details the challenges and opportunities that youth engagement represents. This research explores specific tools that urban planners and other allied professionals make use of when engaging youth-identifying communities. Through a series of semi structured interviews, this project led to the creation of an actionable youth engagement toolkit: Cities For Youth – Toolkit for Youth Engagement in Planning, This professional facing deliverable was supported by the production of a complementary podcast episode as part of the Spacing Radio series. Jointly, these two pieces look to expand on professional perspectives on youth engagement while bringing this issue to the forefront of urban journalism.
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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 | 0.035 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.015 |
| Scholarly communication | 0.013 | 0.008 |
| Open science | 0.003 | 0.031 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".