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Contract Compliance in the United States and Canada

2007· book-chapter· en· W2495895373 on OpenAlexaboutno aff
Christopher McCrudden

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldSocial Sciences
TopicLabor Movements and Unions
Canadian institutionsnot available
Fundersnot available
KeywordsProcurementGovernment procurementLinkage (software)Equity (law)Compliance (psychology)Affirmative actionBusinessGovernment (linguistics)World War IIPolitical sciencePublic administrationLawMarketing

Abstract

fetched live from OpenAlex

Abstract This chapter discusses the development of procurement linkage as a tool for tackling employment discrimination based on race, beginning in the United States during the Second World War, and continuing during the 1950s and 1960s, mutating into a mechanism for securing affirmative action. It traces the development of this approach up to the early 1990s. The expansion of this approach to cover other groups in the United States is then considered, in particular the use of procurement to encourage the development of access by disabled workers to information technology. The chapter also examines the development of a type of procurement linkage in Canada that mirrors that of the United States: schemes that link the award of government contracts with attempts to secure ‘employment equity’ in employment for various groups, referred to as ‘contract compliance’. It is shown how the International Labour Organization (ILO) has adopted this contract compliance approach.

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)0.002
metaresearch head score (Gemma)0.004
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: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.126
Threshold uncertainty score0.918

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0120.003
Scholarly communication0.0060.001
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0120.001

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 head0.305
Teacher spread0.252 · 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
GenreOther

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
Published2007
Admission routes1
Has abstractyes

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