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Record W2803177187 · doi:10.4337/9780857939319.00008

A review of two decades of employment equity in Canada: progress and propositions

2014· review· en· W2803177187 on OpenAlexaboutno aff
Eddy S. Ng, Rana Haq, Diane‐Gabrielle Tremblay

Bibliographic record

VenueEdward Elgar Publishing eBooks · 2014
Typereview
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)BusinessPolitical scienceLaw

Abstract

fetched live from OpenAlex

Employment equity was officially sanctioned in 1986 with the passage of the federal Employment Equity Act (EEA). It follows a report from the Royal Commission of Inquiry on Equality of Employment by Judge Rosalie Abella who deemed that four designated groups, Aboriginal peoples, persons with disabilities, visible minorities and women, face insurmountable barriers leading to discrimination in employment. They were disproportionately excluded from the workplace because of their group membership, and most of the barriers they faced were systemic in nature. Consequently, the EEA was put in place to eliminate barriers in the workplace so that no person is denied employment opportunities for reasons unrelated to ability. The intent is to allow everyone to contribute evenly to the success of their employers and to the economic and social well-being of all Canadians. The term 'employment equity' was developed by Judge Abella, who headed the Royal Commission, to describe a distinctly Canadian process for achieving equality in all aspects of employment. The term was meant to distinguish the process from the primarily American affirmative action model. It was felt that the phrase 'affirmative action' elicited negative reactions and resistance from many because it has become associated with interventionist government policies and the imposition of quotas (Mentzer, 2002). Abella argues that, ultimately, it matters little which term is used since both terms refer to 'employment practices designed to eliminate barriers and to provide in a meaningful way equitable opportunities in employment' (Abella, 1984, p. 7).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.907
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.059
GPT teacher head0.397
Teacher spread0.338 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations10
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEdward Elgar Publishing eBooksSame topicLabor Movements and UnionsFrench-language works237,207