Shrinking Cities, Shrinking Households, or Both?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Household size decline accounts for a substantial portion of population loss in shrinking cities, yet little research has focused on it. Much of the literature presents a simple growth/decline binary that is largely determined via population figures. In this paper, we highlight the importance and assess the impact of household size changes on population decline, and determine what types of household size declines are more acute in shrinking cities than other locales. We find that elderly households and households with school‐aged children are under‐represented in shrinking cities, while households with pre‐school‐aged children are over‐represented. More tellingly, we find the biggest source of household‐related loss in shrinking cities to be the growth of single‐person households now living in houses that were once home to entire families. These findings puncture the binary on which much of the shrinking cities discourse is based. The population dynamics of most cities are subtler than either practitioners or critical scholars assert. We argue that plans and development strategies for shrinking cities should reflect a range of demographic changes, including outmigration and internal household restructuring.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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