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Record W4408363209 · doi:10.1111/cag.70006

Sharing cities with the future: How concerned are young Montrealers today about the implications of their residential choices for future generations?

2025· article· en· W4408363209 on OpenAlexafffundvenueabout
M Reid, Matthias Fritsch, Rebecca Tittler, Craig Townsend, William M. Bukowski, Ryan J. Persram, Jochen A.G. Jaeger

Bibliographic record

VenueCanadian Geographies / Géographies canadiennes · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsToronto Metropolitan UniversityConcordia University
FundersConcordia University
KeywordsEnvironmental planningEconomic geographyGeography

Abstract

fetched live from OpenAlex

Abstract Residential preferences for single‐family homes are a key driver of urban sprawl. Using a stated‐preference survey among university students in Montreal, we explored how participants’ residential preferences are related to their perceptions of urban sprawl and intergenerational justice. A surprisingly large proportion of participants knew very little about urban sprawl. Preference for single‐family homes was not particularly pronounced. Preferences for suburban and urban housing options were similarly strong. Evidence was insufficient to conclude that perceptions of urban sprawl were associated with housing choices, but results indicated promising avenues for further research. Residential preferences were more strongly related to perceptions of future urban sprawl than current urban sprawl. Participants were equally concerned about their own futures and those of future generations, and both concerns were associated with residential preferences. Individuals are open to more sustainable housing options. It will be crucial to increase awareness among landowners, developers, urban planners, and renters about the intergenerational significance of housing choices.

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)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.691
Threshold uncertainty score0.614

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.010
GPT teacher head0.226
Teacher spread0.216 · 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 designQualitative
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

Citations1
Published2025
Admission routes4
Has abstractyes

Explore more

Same venueCanadian Geographies / Géographies canadiennes→Same topicMigration, Aging, and Tourism Studies→French-language works237,207→