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Record W4302339851

Putting on the moves: Individual, household, and community-level determinants of residential mobility in Canada

2013· article· en· W4302339851 on OpenAlexaboutno aff
Ravi Pendakur, Nathan Young

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Aging, and Tourism Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyDemographic economicsRegional scienceSociologyEconomics
DOInot available

Abstract

fetched live from OpenAlex

<b>Background</b>: Internal residential mobility is an important contributor to economic vitality, helping to address gaps in the labour market, assisting regions to develop comparative advantages, and encouraging the circulation of skills, capital, and networks within a country. Mobility is, however, a complex sociological phenomenon influenced by individual, household, and community-level variables. <b>Objective</b>: This article examines the combined impact of individual, household, and community characteristics on both short- and long-distance residential mobility in Canada. The study is motivated by a broader concern with economic development and community vitality, particularly in smaller towns and cities that have recently struggled to attract newcomers. <b>Methods</b>: A series of multilevel random intercept regression models are run on Canadian census data from 2006. Canada-wide findings are compared to those for five sizes of community - from small towns with fewer than 10,000 people to major metropolitan cities. <b>Results</b>: Despite the continued growth of major metropolitan areas, city size is not an attractor in and of itself. Rather, one of the most powerful draws for both small towns and large cities is the diversity of the existing population, as measured by the proportion of residents who are immigrants and/or visible minorities. <b>Conclusions</b>: These findings challenge some long-held stereotypes about rural living, and suggest that rural development strategies ought to include measures for enhancing diversity as a means of attracting all types of internal migrants to small towns and cities.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.038
Threshold uncertainty score0.930

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.379
GPT teacher head0.511
Teacher spread0.131 · 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 teacher head, 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

Citations2
Published2013
Admission routes1
Has abstractyes

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