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How do we boost employment outcomes for neurodiverse Albertans?

2018· article· en· W6922191834 on OpenAlexaboutno aff

Bibliographic record

VenueUniversity of Calgary · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsUnemploymentWorkforceFace (sociological concept)WelfareWork (physics)Stigma (botany)EmployabilityConvention

Abstract

fetched live from OpenAlex

Despite the supports that have been put in place, Canadians with developmental disabilities (DD) continue to face obstacles in gaining and maintaining employment. In 2012 two out of three Canadians with DD were out of the workforce and not looking for a job. This dismal statistic means that a large number of capable people are chronically unemployed, a situation that leads to poorer quality of life, with accompanying declines in cognitive function and general well-being. For these neurodiverse Canadians, the cascading effects of unemployment include financial insecurity, poor self-esteem, less ability to live independently and lower community participation. For employers, it means that a pool of diverse talent and resources that would benefit their companies is untapped. Of all disabilities, Canadians with DD face the worst employment levels. Educating employers about neurodiversity and incentivising them to make accommodations in hiring practices and in the workplace would go far toward reducing the number of jobless neurodiverse people. As a signatory to the UN Convention on the Rights of Persons with Disabilities, Canada is expected to provide inclusive and accessible job training, education and labour market opportunities. Yet, labour market activation programs, welfare reforms and equality laws have so far failed to make a difference in the unemployment numbers. A recent study reveals that the top three barriers to unemployment for neurodiverse Albertans include employers’ knowledge, attitude, capacity and management practices; a late start to the concept of work among people with DD; and the stigma of their disability. Programs to remedy the situation abound at the federal and provincial levels and lately, the focus has been shifted to employer education initiatives. Much remains to be done, however, and this communiqué offers suggestions for policy changes that may benefit all parties concerned. One policy could entail changing the design of income assistance programs like Assured Income for the Severely Handicapped (AISH) to remove disincentives to work, such as ensuring continued access to important health benefits. Governments could also offer financial incentives such as wage subsidies and tax credits to employers who hire neurodiverse people, as well as provide monetary incentives for neurodiverse Canadians who wish to be self-employed. Training programs could be available for employers to teach them the value of having a diverse workforce, as well as instructing them in how their companies can become inclusive and accessible. Putting the proper supports in place in the early years would assist neurodiverse high-school youth to participate in career planning, work internships and job training. Helping Canada’s neurodiverse population to get and keep jobs provides benefits to the economy in terms of increased GDP, to employers in terms of talent and ability, and to people with DD who will enjoy a higher quality of life, greater self-esteem and reduced stigma and isolation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.784

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.036
GPT teacher head0.285
Teacher spread0.249 · 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 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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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