MétaCan
Menu
Back to cohort
Record W2114420595 · doi:10.1017/s0047279407001481

Neighbourhood Ethnic Concentration and Discrimination

2007· article· en· W2114420595 on OpenAlex

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

VenueJournal of Social Policy · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsUniversity of British ColumbiaUniversity of Toronto
Fundersnot available
KeywordsEthnic groupLocale (computer software)ImmigrationNeighbourhood (mathematics)Demographic economicsEthnic discriminationEthnically diverseChinese americansSociologyGeographyPsychologyDemographyEconomics

Abstract

fetched live from OpenAlex

We investigate the association between the residential concentration of Chinese in Toronto and discrimination as experienced and perceived by Chinese immigrant residents. A unique aspect of this study is our focus on perceived employment discrimination. We find that Chinese immigrants living in neighbourhoods with a high concentration of other Chinese residents are more likely to perceive employment discrimination against Chinese people as a group, and are more likely to report exposure to ethnically motivated verbal assault, than are Chinese immigrants living elsewhere. Our results are consistent with studies of other populations. However, we argue that theory and policy related to ethnic concentration and discrimination should recognise that effects of ethnic concentration on discrimination are likely to vary with the ecological setting under investigation (for example, neighbourhoods versus larger areas), as well as by size of locale (city, region, or country), and the ethnic groups involved.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.810
Threshold uncertainty score0.343

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.029
GPT teacher head0.382
Teacher spread0.353 · 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