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Record W2153175120 · doi:10.3109/09638280903023389

Women with disabilities' experiences of government employment assistance in Canada

2009· article· en· W2153175120 on OpenAlexaffabout
Vera Chouinard

Bibliographic record

VenueDisability and Rehabilitation · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsMcMaster University
Fundersnot available
KeywordsGovernment (linguistics)SubsidyWork (physics)Supported employmentIndividualismWagePsychologyPolitical scienceBusinessPublic relationsLabour economicsEconomicsEngineering

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this article is to explore women with disabilities' experiences of government employment assistance in Canada. METHOD: The article draws on the results of an online survey conducted in 2006. Data were coded and analysed according to key themes. RESULTS: The results indicate that many of the women with disabilities who responded to the survey regarded the employment assistance they have received as of very limited importance to their abilities to find and keep paid work. Their comments suggest that existing forms of government employment assistance, such as the provision of wage subsidies to employers, may be of limited effectiveness in enabling at least some women with disabilities to find and keep paid work. The women's comments point to the limitations of existing employment assistance strategies including the need to shift program emphases away from individualistic models aimed at 'reforming the worker' and toward systemic barriers to employment. CONCLUSIONS: The article concludes by discussing the implications of survey results for future research and strategies for improving the types of employment assistance available to women with 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.828

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.013
GPT teacher head0.277
Teacher spread0.264 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations11
Published2009
Admission routes2
Has abstractyes

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