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Record W2128716804 · doi:10.1080/00420980120080844

Immigrant Settlement Patterns in Metropolitan Chicago

2001· article· en· W2128716804 on OpenAlexaff
K. Bruce Newbold, John Spindler

Bibliographic record

VenueUrban Studies · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicUrban, Neighborhood, and Segregation Studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMetropolitan areaMicrodata (statistics)ImmigrationGeographyDemographic economicsCensusPopulationCohort effectCohortPublic useDistribution (mathematics)DemographySettlement (finance)Economic geographySocioeconomicsRegional scienceEconomic growthPolitical scienceSociologyEconomicsStatisticsArchaeology

Abstract

fetched live from OpenAlex

The distribution of the immigrant population reflects a dynamic system that evolves over time and differs by arrival cohort and national origin. Government policies, new information, employment opportunities, housing, racism or other cultural effects may be responsible for subsequent migrations and changes in the population distribution of the foreign-born. Using data from the 5 per cent Public Use Microdata Sample, 1990, this paper compares settlement patterns of immigrant arrival cohorts within metropolitan Chicago, filtered through the lens of Zelinksy and Lee's heterolocalism framework. Cohorts are defined based on period of arrival in the US and by age. The spatial geography associated with each arrival cohort is constructed with respect to areas of relative concentration within the metropolitan area.

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)0.000
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.056
GPT teacher head0.345
Teacher spread0.289 · 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

Citations29
Published2001
Admission routes1
Has abstractyes

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