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Record W2894304533 · doi:10.1080/19438192.2018.1523092

Examining the factors that affect the employment status of racialised immigrants: a study of Bangladeshi immigrants in Toronto, Canada

2018· article· en· W2894304533 on OpenAlex
Marshia Akbar

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSouth Asian Diaspora · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Ethnicity, and Economy
Canadian institutionsYork University
FundersSocial Sciences and Humanities Research Council of CanadaYork University
KeywordsImmigrationAffect (linguistics)Demographic economicsGeographySociologySocioeconomicsEconomics

Abstract

fetched live from OpenAlex

Analysing data from the 2006 Canadian census, the paper identifies various social characteristics that influence Bangladeshi immigrants’ employment status in Toronto, particularly their propensity to be self-employed and outside the paid labour force rather than paid employees. The analysis contributes to understanding why racialised immigrants take different paths to participating in the Canadian labour market. The results of regression analysis suggest that women are more likely to be out of the paid labour force and less likely to be self-employed or paid employees than their male counterparts. Young Bangladeshis with a university degree are least likely to withdraw from the paid labour force. Older Bangladeshis and those with longer length of residence in Canada are more likely to be self-employed. The likelihood of being out of the paid labour force increases as Bangladeshi immigrants age, and with less education and decreases for those with longer residence in Canada.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.447

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 communication0.0000.000
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 head0.040
GPT teacher head0.294
Teacher spread0.254 · 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