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Record W2114006926 · doi:10.1017/s1474746407003636

‘Work First’ and Immigrants in Toronto

2007· article· en· W2114006926 on OpenAlexaffabout
Andrew Mitchell, Ernie Lightman, Dean Herd

Bibliographic record

VenueSocial Policy and Society · 2007
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDisadvantageImmigrationEarningsWageWelfareWork (physics)Demographic economicsLabour economicsIntervention (counseling)SociologyPolitical scienceEconomicsPsychologyLaw

Abstract

fetched live from OpenAlex

This paper examines the experiences of immigrants in Toronto as they pass through, and leave, Ontario Works (OW), a ‘Work First’ approach to social assistance that prioritizes rapid labour force attachment. We examine the Ontario Works activities of immigrants, compared to native born Canadians, and their respective post-OW job characteristics. We find that immigrants experience a significant relative wage disadvantage after participation, and substantially less wage growth when moving to the second post-welfare job. We conclude that Ontario Works, like most ‘work first’ employment programs, is ill-suited to addressing earnings disadvantage among immigrants. We suggest that programs ‘beyond work first’, though not targeted specifically towards immigrants, might nevertheless offer more assistance. The recurring wage disadvantage, however, would remain unaddressed and might require more direct intervention.

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 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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.353
Threshold uncertainty score1.000

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 studies0.0010.000
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 head0.041
GPT teacher head0.434
Teacher spread0.393 · 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 teacher head, not a consensus.

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

Citations12
Published2007
Admission routes2
Has abstractyes

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