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Record W1745144391 · doi:10.3233/wor-2007-00651

Employment after spinal cord injury: The impact of government policies in Canada

2007· article· en· W1745144391 on OpenAlexaffabout
Lyn Jongbloed, Catherine L. Backman, Susan Forwell, Christine Carpenter

Bibliographic record

VenueWork · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicHealthcare innovation and challenges
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLegislationGovernment (linguistics)Equity (law)PoliticsReasonable accommodationPolitical scienceBusinessEconomic growthIncome SupportPublic administrationGeneral partnershipWork (physics)EconomicsLaw

Abstract

fetched live from OpenAlex

The British Columbia Paraplegic Association (BCPA) sought a research partnership to evaluate where its activities should be focused. A survey of members with disabilities of the BCPA included questions on employment and identified three priorities related to employment. These were the need for assistance in finding appropriate work, the impact of policies of government and insurance agencies, and attitudes of employers. This paper examines the social and political environment related to employment following spinal cord injury in British Columbia, Canada. There is no coherent set of goals underlying government employment and income programs in Canada. Incremental development of particular employment and income programs during the 20th century led to a patchwork of policies and programs, which deal with people differently according to the cause of their disability. Federal and provincial governments have attempted to educate employers and reduce barriers to employment of those with disabilities by focusing on anti-discrimination legislation and individual rights (e.g. the Employment Equity Act and the Canadian Human Rights Act). However, people with disabilities face non-accommodating environments, inadequate income support, lack of opportunities and little political influence which stem from an unfair distribution of societal resources, not from discrimination. Joint efforts of the BCPA and other disability organizations are likely to have the most impact on legislative changes.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.942

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.005
Science and technology studies0.0110.003
Scholarly communication0.0050.001
Open science0.0020.003
Research integrity0.0010.002
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 head0.044
GPT teacher head0.396
Teacher spread0.352 · 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 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

Citations33
Published2007
Admission routes2
Has abstractyes

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