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Record W2467877307 · doi:10.1111/capa.12171

Employment equity in Canada: Making sense of employee discourses of misunderstanding, resistance, and support

2016· article· en· W2467877307 on OpenAlexaboutno aff
Rosemary A. McGowan, Eddy S. Ng

Bibliographic record

VenueCanadian Public Administration · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicGender Diversity and Inequality
Canadian institutionsnot available
Fundersnot available
KeywordsEquity (law)LegislationPolitical sciencePay EquityPublic relationsResistance (ecology)PerceptionSociologyPsychologyLabour economicsEconomicsLaw

Abstract

fetched live from OpenAlex

Abstract Employment equity initiatives – redressing past inequities or discrimination by promoting the hiring of members of underrepresented groups – are controversial and divisive. Although a national Gallup poll (1993) indicated 74 % of Canadians felt a person's qualifications should solely determine hiring decisions, many have little knowledge and understanding of the issue. Adopting a discourse analytic framework, this research explores employees’ understandings and perceptions of an employment equity initiative in a mid‐sized Canadian organization. Employment equity was seen as problematic and not well understood, and individuals eligible for employment equity initiatives were marginalized. This study contributes to identifying the misunderstandings and underlying sources of tensions with employment equity principles, legislation and administrative regimes.

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)0.011
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.199
Threshold uncertainty score0.929

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.022
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.006
Science and technology studies0.0580.028
Scholarly communication0.0170.004
Open science0.0030.009
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0030.000

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 head0.146
GPT teacher head0.343
Teacher spread0.197 · 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 designQualitative
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

Citations9
Published2016
Admission routes1
Has abstractyes

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