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Record W7057213379

The Impact of Regionally Differentiated Entitlement to EI on Charter-Protected Canadians

2011· article· en· W7057213379 on OpenAlexaboutno aff

Bibliographic record

VenueBerkley Law Scholarship Repository (University of California, Berkeley) · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsEntitlement (fair division)UnemploymentCharterDisadvantageWork (physics)PoliticsDifferential treatmentTemporary work
DOInot available

Abstract

fetched live from OpenAlex

Under Canada’s Employment Insurance (EI) program, access to unemployment benefits varies according to the regional unemployment rate. Previous studies have shown that this regime works to the disadvantage of certain provinces and urban areas. In this paper we measure the impact of the variable regional entrance requirements on specific minority workers, including visible minorities, linguistic minorities, recent immigrants, and naturalized citizens. We find that over the period 2000-2010, the regional variation in access to EI results in certain minority workers being required to work modestly more hours to qualify for EI than the average worker. Though the findings with regard to minority workers are modest, the differential treatment of workers by region remains problematic as a matter of both fairness and policy design. Because there are political barriers blocking the elimination or modification of the regional entrance requirements in Parliament, it may be fruitful to turn to the courts in pursuing reform. We provide a legal analysis under s. 15 of the Canadian Charter of Rights and Freedoms to investigate whether the impact of the regional entrance requirements could be considered unconstitutional adverse effects discrimination. We conclude that while the data does not support a constitutional claim today, if the differential, negative impact on minority workers increases in the future the chances of an equality rights challenge succeeding would also grow.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.372
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.019
GPT teacher head0.225
Teacher spread0.206 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

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