Children’s rights to the city: growth and decline in Aotearoa-New Zealand
Bibliographic record
Abstract
This paper investigates the evolving experiences of urban childhood framed within the context of children's rights to the city, and in relation to significant societal changes such as technological advancements, educational pressures, enhanced mobility and urban development. Through our three-generational family study we examine if cities are becoming more or less conducive to children's access and agency in relation to their right to the city. Comparing children's contemporary well-being with that of the past two generations highlights the shifts in city access, community connections, and children's neighbourhood relationships. Our findings reveal a complex interplay between enhancements in children's rights such as educational opportunities and the challenges posed by contemporary urban living, such as reduced independence and increased safety concerns. Conducted in Wellington, New Zealand, the study identifies that the rhetoric of children as active participants in city life contrasts markedly with the reality of their increasingly constrained neighbourhood and the wider city access, underscoring the need for a nuanced understanding of children's well-being in urban settings. We call for a re-evaluation of how cities can better accommodate the needs and rights of children, advocating for a more inclusive approach that helps reinstate and advance city children’s autonomous rights and wellbeing.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.006 | 0.006 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".