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Towards socio‐spatial inclusion? Disabled people, neoliberalism and the contemporary labour market

2006· article· en· W1995397155 on OpenAlexafffund
Robert Wilton, Stephanie Schuer

Bibliographic record

VenueArea · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsAccommodationConceptualizationDisabled peopleFace (sociological concept)Work (physics)Inclusion (mineral)Neoliberalism (international relations)Social securitySocial exclusionLabour economicsBusinessSociologyPublic relationsEconomic growthEconomicsPolitical scienceMarket economyPolitical economySocial sciencePsychology

Abstract

fetched live from OpenAlex

In many Western countries, disability assistance programmes have been restructured to encourage paid work. This paper examines the opportunities and barriers facing disabled people entering the labour market. Using data from semi‐structured interviews, the study explores employers’ conceptualization and treatment of disabled workers. While meaningful accommodation does occur, less promising outcomes are also common. For example, some disabled people face exclusion from service work on grounds that have little to do with the capacity to perform the essential functions of specific jobs. Others face exploitation in downgraded service occupations. Moreover, funding cuts and market discipline in public and non‐profit organizations limit their capacity to accommodate disabled workers. While employment can offer material security and social status, successful employment for many disabled people cannot occur without an effective challenge to the contextual constraints of non‐accommodating workplaces and labour processes.

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)0.004
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.041
Scholarly communication0.0090.007
Open science0.0010.009
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.028
GPT teacher head0.307
Teacher spread0.279 · 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

Citations62
Published2006
Admission routes2
Has abstractyes

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