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Record W1986820338 · doi:10.1177/1078087404273443

The Construction of the Geography of Immigration as a Policy Problem

2005· article· en· W1986820338 on OpenAlex
Yasmeen Abu‐Laban, Judith A. Garber

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueUrban Affairs Review · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsImmigrationCensusSettlement (finance)NewspaperImmigration policyBiological dispersalGovernment (linguistics)Construct (python library)GeographySociologyEconomic growthPolitical sciencePublic administrationLawEconomicsDemographyPopulation

Abstract

fetched live from OpenAlex

The release of 2000 U.S. Census and 2001 Canadian Census data sparked significant interest in immigrant dispersal outside major urban centers. This article analyze show the meaning of immigration settlement patterns is socially constructed by using a comparative textual analysis of newspaper coverage of census findings as well as government documents and think tank studies. The authors argue that in Canada, immigration settlement is interpreted as a national policy problem necessitating federal state intervention, whereas presentations in U.S. print media construct immigration settlement as the outcome of choices made by individual immigrants and, thus, as local policy problems. In each case, construction of immigrant dispersal draws on national mythologies and omits alternative interpretations of the geography of immigrant settlement.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score0.407

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.007
GPT teacher head0.276
Teacher spread0.269 · 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