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Record W3115586055 · doi:10.15353/cjds.v8i5.567

Critical Reflections on the Process of Developing a Resource Manual for Service Providers Working with Immigrants & Refugees with Disabilities

2019· article· en· W3115586055 on OpenAlexaffvenueabout
Kaltrina Kusari, Yahya El‐Lahib, Natalie Spagnuolo

Bibliographic record

VenueCanadian Journal of Disability Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsYork UniversityUniversity of Calgary
Fundersnot available
KeywordsRefugeeImmigrationNexus (standard)Service delivery frameworkService providerSettlement (finance)Resource (disambiguation)Service (business)SociologyPublic relationsPolitical scienceBusinessComputer scienceLaw

Abstract

fetched live from OpenAlex


 
 
 
 This paper presents critical reflections on the process of developing a resource manual for service providers who work with immigrants/refugees with disabilities. The development of this manual gave us insight into existing programs which address the intersection between immigration and disability, as well as the paradigms that guide services which target immigrants/ refugees with disabilities. We approached the manual through a postcolonial disability framework which facilitated a critical examination of the operation of ableist and neocolonial discourses within and through settlement practices. The main findings highlight the “siloed” nature of service delivery for immigrants/refugees with disabilities. Findings also illustrate how relevant provincial strategies do not address the intersection between immigration and disability, but rather focus on using immigration to reach other provincial targets. These findings add to the body of existing, albeit scarce, literature which focuses on the immigration-disability nexus and provide important implications for policymaking and service delivery for a largely hidden population of immigrants 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 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)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.864
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
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 head0.110
GPT teacher head0.400
Teacher spread0.290 · 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 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
Published2019
Admission routes3
Has abstractyes

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