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Record W1570701305

The Rise in Low-income Rates Among Immigrants in Canada

2003· preprint· en· W1570701305 on OpenAlexaffabout
Feng Hou, Garnett Picot

Bibliographic record

VenueRePEc: Research Papers in Economics · 2003
Typepreprint
Languageen
FieldSocial Sciences
TopicMigration and Labor Dynamics
Canadian institutionsStatistics Canada
Fundersnot available
KeywordsImmigrationFalling (accident)Demographic economicsCensusGeographyLow incomeDemographyEconomicsSociologyPopulationMedicine
DOInot available

Abstract

fetched live from OpenAlex

This study uses census data to focus on low-income among immigrants, and asks a number of questions: (1) have low-income rates increased among successive cohorts of entering immigrants, both in absolute terms and relative to the Canadian born (they have), (2) is this increase due to changes in their characteristics (e.g. education, age, source country, language etc.), (3) do low-income rates fall as new immigrants acquire Canadian experience, and are there signs that low-income rates fall faster among the more recent entering cohorts with the higher entry level rates, resulting in some "catch-up", and (4) in the major Canadian cities, to what extent was the deterioration in the city level low-income rates during the 1990s concentrated among immigrants? The analysis covers the period from 1980 to 2000, and focuses on change between 1980 to 1990, and 1990 to 2000, years that are roughly at business cycle peaks. The study finds that low-income rates among "recent" immigrants (in Canada for less than five years) almost doubled between 1980 and 1995, and then fell during the strong recovery of the late 1990s. However, when focusing on outcomes at business cycle peaks (1980, 1990 and 2000) to establish comparable long-term, low-income rates rose continuously for each successive cohort of immigrants. Furthermore, the gap at entry in their low-income rate relative to the Canadian-born also rose over the 1980-2000 period. The changing composition of "recent" immigrants with respect to language, source country, family type and age accounted for, at most, half of the rise in the low-income rate among this group, and likely substantially less than that. Most of the increase was a result of the widespread rise in low-income among recent immigrants in all age groups, family types, language groups, education groups, and most of the more significant (numerically) source regions, notably Africa and the Asian source regions. The peak to peak rise in the low-income rate between 1980 and 2000 was not restricted to recent immigrants, and was observed (to a lesser extent) among immigrants who had been in Canada for up to 20 years. Low-income rates among immigrants tend to fall with time spent in Canada. Furthermore, among the more recent entering cohorts with the higher low-income rates at entry, the rate of decline is faster. There is evidence of a "catch-up" (to earlier cohorts) among the more recent entering cohorts. However, low-income rates remain higher among immigrant cohorts of the late 1980s and early 1990s than among their counterparts in the 1970s (comparing groups with a comparable number of years in Canada). The rise in the low-income rates in the three major Canadian cities, and in Ontario and B.C. during the 1990s in particular, was largely concentrated among the immigrant population. Basically, low-income rates have been falling over the past two decades among the Canadian born, and rising among immigrants. A discussion of

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)0.001
metaresearch head score (Gemma)0.003
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 score0.026
Threshold uncertainty score0.186

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.005
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.016
GPT teacher head0.311
Teacher spread0.295 · 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

Citations127
Published2003
Admission routes2
Has abstractyes

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Same venueRePEc: Research Papers in EconomicsSame topicMigration and Labor DynamicsFrench-language works237,207