MétaCan
Menu
Back to cohort
Record W1822763094 · doi:10.1177/0042098012443859

Testing and Extending the Escalator Hypothesis: Does the Pattern of Post-migration Income Gains in Toronto Suggest Productivity and/or Learning Effects?

2012· article· en· W1822763094 on OpenAlexaffabout
K. Bruce Newbold, W. Mark Brown

Bibliographic record

VenueUrban Studies · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMetropolitan areaProductivityDemographic economicsLabour economicsUrban hierarchyEconomicsEconomies of agglomerationHierarchyEconomic geographyGeographyEconomic growthSociologyDemographyPopulation

Abstract

fetched live from OpenAlex

Workers earn incomes that are significantly higher in large metropolitan areas as compared with other locations in the urban hierarchy, reflecting both agglomeration economies and variation in the composition of skills and abilities across space. What benefits accrue to in-migrants to large urban areas? Fielding’s concept of the escalator region provides one way to evaluate the role of large metropolitan areas vis-à-vis the labour market, occupational mobility and migration. The purpose of this paper is to evaluate whether young adult migrants to Toronto aged 20–29 receive income benefits that are higher than those associated with other migrants or stayers. Results indicate that Toronto in-migrants receive an income benefit consistent with a productivity effect that is greater than the income benefit received by migrants elsewhere in the system or those who did not migrate. However, it does not appear that migration leads to an acceleration in income gains.

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)0.002
metaresearch head score (Gemma)0.006
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 score0.074
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.049
GPT teacher head0.318
Teacher spread0.270 · 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

Citations12
Published2012
Admission routes2
Has abstractyes

Explore more

Same venueUrban StudiesSame topicUrban, Neighborhood, and Segregation StudiesFrench-language works237,207