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Record W7099124521

personal views. ADDRESSING SYSTEMIC RACIAL DISCRIMINATION IN EMPLOYMENT:

2002· article· en· W7099124521 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsnot available
Fundersnot available
KeywordsRacismLegislatureEquity (law)Human rightsRedressEmployment discriminationPublic policyTribunalHealth equity
DOInot available

Abstract

fetched live from OpenAlex

THE HEALTH CANADA CASE AND IMPLICATIONS OF LEGISLATIVE CHANGE The 1997 Human Rights Tribunal decision on systemic racial discrimination at Health Canada, specifically addressing glass-ceiling barriers to the promotion of visible minorities to senior management, provides an effective illustration of the subtle and elusive nature of this form of discrimination, the complex evidence required for legal proof, and the rationale for employment-equity remedies. Public participation was critical to the case. It helped identify and interpret critical testimony and documents, mobilize resources for an employee survey and expert testimony, and develop a detailed remedial proposal. Under the 1996 amendments to the Employment Equity Act and the Canadian Human Rights Act responsibility for systemic discrimination has changed, replacing the demonstrated potential of the human-rights complaints process with the broader coverage of a new audit-based employment equity process. The Health Canada experience suggests that a key to this tradeoff is whether limited opportunities for public input can be enhanced. Implications for legal strategies and broader policy to address systemic racial discrimination are discussed. ADDRESSING SYSTEMIC RACIAL DISCRIMINATION IN EMPLOYMENT: THE HEALTH CANADA CASE AND IMPLICATIONS OF LEGISLATIVE CHANGE

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.635
Threshold uncertainty score0.733

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0120.003
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0090.006
Insufficient payload (model declined to judge)0.0370.005

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 head0.053
GPT teacher head0.276
Teacher spread0.223 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2002
Admission routes1
Has abstractyes

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