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Record W2007602111 · doi:10.1177/0002716209344172

The New Urbanity: The Rise of a New America

2009· article· en· W2007602111 on OpenAlexaboutno aff
Arthur C. Nelson

Bibliographic record

VenueThe Annals of the American Academy of Political and Social Science · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing Market and Economics
Canadian institutionsnot available
Fundersnot available
KeywordsUrbanityBaby boomBoomOil boomQuarter (Canadian coin)Metropolitan areaPopulationBaby boomersGeographyDemographic economicsEconomic growthEconomyEconomicsSocioeconomicsDemographySociologyEngineeringArchaeology

Abstract

fetched live from OpenAlex

The period from 2010 to 2030 will see as sweeping a change to America’s metropolitan landscape as the half century after World War II. During the baby boom era, 1946 through 1964, about half of American households were raising children; in 2030, only about a quarter will be. Between 2010 and 2030, the increase in the number of single-person households will be more than double the increase in the number of households with children. A major reason is the aging of the boomers: in 2010, 13 percent of the population will be age sixty-five or over; but by 2030, 19 percent of the population will be. There will be changes in the kind of housing and neighborhoods that households prefer. More than half of all households will prefer housing in neighborhoods that comprise such “urbanity” attributes as transit accessibility; proximity to shopping and restaurants; mixed uses including mixed housing choices; and mixed incomes, ages, and ethnicities. Moving toward this new urbanity will require reconsideration of several policies with roots dating from the baby boom era.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.004
Scholarly communication0.0090.009
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0160.002

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.

Opus teacher head0.081
GPT teacher head0.328
Teacher spread0.247 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations41
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueThe Annals of the American Academy of Political and Social ScienceSame topicHousing Market and EconomicsFrench-language works237,207