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Record W4200081644 · doi:10.15353/cjds.v10i3.818

Challenges Encountered by Newcomers with Disabilities in Canada

2021· article· en· W4200081644 on OpenAlexaffvenueabout
Dora M. Y. Tam, Tracy Smith‐Carrier, Siu Ming Kwok, Don Kerr, Juyan Wang

Bibliographic record

VenueCanadian Journal of Disability Studies · 2021
Typearticle
Languageen
FieldHealth Professions
TopicGlobal Health Workforce Issues
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPopulationPsychologyRepresentation (politics)GerontologySociologyPolitical scienceMedicineDemographyLaw

Abstract

fetched live from OpenAlex

Through a secondary data analysis of administrative data of the Ontario Disability Support Program (ODSP) between 2003 and 2013, we aim to understand the interlocking challenges encountered by newcomers with disabilities in Canada that contribute to this population’s financial hardship. Our findings show that newcomers with disabilities on ODSP were more likely to have post-secondary education, to be older adults, to be married, common-law, and to be female who were divorced, separated, or widowed as compared to Canadian-born recipients, who were more likely to be less educated, younger, single and male. The ratio of Canadian-born to newcomer recipients on the ODSP was high between 2003 and 2013, indicating that the latter were under-represented on the program. Implications for this under-representation support future research to examine the full integration and participation of newcomers with disabilities in Canada.

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)0.007
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 score0.057
Threshold uncertainty score0.414

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0120.002
Scholarly communication0.0040.001
Open science0.0020.005
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 head0.123
GPT teacher head0.407
Teacher spread0.284 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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Same venueCanadian Journal of Disability StudiesSame topicGlobal Health Workforce IssuesFrench-language works237,207