From gentrification to youthification? The increasing importance of young age in delineating high-density living
Why this work is in the frame
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Bibliographic record
Abstract
This paper considers the importance of age in delineating urban space, the latter operationalised as high-density living. Many cities have experienced an increase in inner city living contributing to gentrification. Today, inner cities contain more amenities, public transit and housing options than in the past but there are also growing affordability concerns owing to rising prices. Especially young adults, sometimes dubbed Millennials, are making location decisions in a context of lower employment security, higher costs and continuing high-density re-development that now extends into suburban areas in some cases. The analysis in this paper shows evidence of a youthification process that results in an increasing association of high-density living with the young adult lifecycle stage. The higher density areas remain young over time as new young adults move into neighbourhoods where there are already young people living, and they move out if their household size increases. Youthified spaces have become characterised by small housing units that are not generally occupied by households with children. Additionally, some areas are exhibiting generational bifurcation as both older and younger adults live in some higher density areas. Youthification is driven by a combination of lifestyle, demographic, macro-economic and housing market changes that require further investigation. The youthification process is not replacing, but occurring alongside, gentrification and points to young age as a delineator of high-density living becoming more important over time. However, immigration, measures of social class and household size still remain the most important explanatory variables of high-density living.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it