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Record W2071937614 · doi:10.4236/tel.2015.51011

Income Disparities: The Case of Unskilled Workers in Canada (1996-2010)

2015· article· en· W2071937614 on OpenAlex
Samir Amine, Phillippe Scrimger

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

VenueTheoretical Economics Letters · 2015
Typearticle
Languageen
FieldHealth Professions
TopicEmployment and Welfare Studies
Canadian institutionsUniversité de MontréalCanadian Industrial Relations AssociationUniversité du Québec en Outaouais
Fundersnot available
KeywordsWorkforceCategorical variableDisadvantageDemographic economicsEconomicsWelfareInequalityLabour economicsPopulationEconomic growthPolitical scienceSociologyDemography

Abstract

fetched live from OpenAlex

In this paper we analyse the gaps in economic welfare that exist between skilled and unskilled labor in Canada. Following the work of Chardon [1] [2] and Amossé and Chardon [3], we use compe- tency levels as defined in the National Classification of Occupations to distinguish these two groups and then analyse the income disparities that exist between them. Our main findings show that unskilled workers are worse off economically than their skilled counterparts and that the Canadian workforce seems to be more bipolarized than the Canadian population as a whole. We also find strong intra-categorical inequalities within unskilled labor, workers from the sales and services occupational domain being at a disadvantage relative to their peers in other occupational groups. Finally, we show that state intervention, through taxation and social transfers, plays an important role in tightening the inter-categorical and intra-categorical income gaps.

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 score0.170
Threshold uncertainty score0.400

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 studies0.0000.001
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 head0.028
GPT teacher head0.304
Teacher spread0.276 · 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