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Record W1525972155

Whose Fault Is It? Asking the Right Questions When Trying to Address Discrimination

2011· article· en· W1525972155 on OpenAlexaboutno aff
Belinda Smith, Dominique Allen

Bibliographic record

VenueSSRN Electronic Journal · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicDiscrimination and Equality Law
Canadian institutionsnot available
Fundersnot available
KeywordsObligationDutyLawGovernment (linguistics)Political scienceReasonable accommodationComplaintLaw and economicsSociology
DOInot available

Abstract

fetched live from OpenAlex

The Australian Government’s announcement that it intends to ‘consolidate’ federal anti-discrimination laws has prompted debate about how these laws could be reformed rather than merely reformatted. In this article we compare Australian anti-discrimination laws with equivalent laws in the United Kingdom and Canada to illuminate the conception of discrimination that underpins each law and to prompt further debate about the appropriateness of the Australian regulatory model. If equality is accepted as a social good that benefits all members of a society, regulation that requires responsibility for addressing inequality to be shared is justified. In nations comparable to Australia, such as the UK and Canada, this has been accepted and built into the design of equality laws. The regulatory trend discernible in these jurisdictions is clearly a move away from an individual fault-based model of discrimination regulation like Australia’s which targets only discrimination that can be traced to a wrong-doer. The move is toward a regulatory model that castes a wider net requiring duty-holders not merely to refrain from wrong-doing but also to make at least reasonable efforts to eradicate discrimination and promote equality. In the United Kingdom this is illustrated by the introduction of positive equality duties to supplement the traditional anti-discrimination laws. Alternatively, Canada’s complaint-based system of anti-discrimination laws imposes a limited ‘positive’ obligation on duty holders to provide reasonable accommodation to members of all protected groups. In contrast, Australia’s anti-discrimination laws have not significantly developed since their inception, leaving Australia with ineffective laws and lagging behind international consensus on human rights and equality. To avoid achieving nothing more than ‘consolidation’ of narrow, inadequate, fault-based laws, we need to ask better questions. Addressing inequality is not just about fault.

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)0.032
metaresearch head score (Gemma)0.082
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: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.168

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.082
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0200.044
Scholarly communication0.0150.028
Open science0.0030.008
Research integrity0.0200.035
Insufficient payload (model declined to judge)0.0100.005

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 head0.063
GPT teacher head0.352
Teacher spread0.289 · 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
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

Citations2
Published2011
Admission routes1
Has abstractyes

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Same venueSSRN Electronic JournalSame topicDiscrimination and Equality LawFrench-language works237,207