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Record W3047789538 · doi:10.1017/9781108667371

Ableism at Work

2019· book· en· W3047789538 on OpenAlexaboutno aff
Paul Harpur

Bibliographic record

VenueCambridge University Press eBooks · 2019
Typebook
Languageen
FieldSocial Sciences
TopicElder Abuse and Neglect
Canadian institutionsnot available
Fundersnot available
KeywordsAbleismPsychosocialPrejudice (legal term)Convention on the Rights of Persons with DisabilitiesReasonable accommodationDisfigurementContext (archaeology)PsychologyPsychological interventionCriminologyPolitical scienceSocial psychologyLawConventionPsychiatry

Abstract

fetched live from OpenAlex

The UN Convention on the Rights of Persons with Disabilities promotes ability equality, but this is not experienced in national laws. Australia, Canada, Ireland, the UK and the US all have one thing in common: regulatory frameworks which treat workers with psychosocial disabilities less favorably than workers with either physical or sensory disabilities. Ableism at Work is a comprehensive and comparative legal, practical and theoretical analysis of workplace inequalities experienced by workers with psychosocial disabilities. Whether it be denying anti-discrimination protection to people with episodic disabilities, addictions or other psychological impairments, failing to make reasonable accommodations/adjustments for workers with psychosocial disabilities, or denying them workers' compensation or occupational health and safety protections, regulatory interventions imbed inequalities. Ableism, sanism and prejudice are expressly stated in laws, reflected in judgments, and perpetuated by workplace practices and this book enables advocates, policy makers and lawmakers to understand the wider context in which systems discriminate workers with psychosocial disabilities.

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)0.001
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 score0.037
Threshold uncertainty score0.124

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0370.014

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 head0.024
GPT teacher head0.222
Teacher spread0.198 · 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

Citations31
Published2019
Admission routes1
Has abstractyes

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Same venueCambridge University Press eBooksSame topicElder Abuse and NeglectFrench-language works237,207