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Record W2793081563 · doi:10.22158/rhs.v3n1p7

Transitioning to Adulthood in Sweden: Comparing the Priorities of Immigrant Youths with Disabilities and Caregivers, from Middle-Eastern Countries

2018· article· en· W2793081563 on OpenAlexaboutno aff
Elisabet Björquist, Nihad A. Almasri, Inger Hallström, Eva Nordmark

Bibliographic record

VenueResearch in Health Science · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicDisability Education and Employment
Canadian institutionsnot available
Fundersnot available
KeywordsImmigrationPsychologyDemographyMedicineGerontologyPolitical scienceSociology

Abstract

fetched live from OpenAlex

Background: There is limited knowledge about perceived challenges during the transition to adulthood among immigrant youths who are originally from Arabic-speaking countries but now residing in Sweden. Aim: The aim of this study was to describe self-identified problems encountered by immigrant youths with disabilities from Middle Eastern countries who were living in Sweden during their transition to adulthood and to compare these descriptions to the problems identified by their caregivers. Methods: Seventeen semi-structured interviews using the Canadian Occupational Performance Measure were conducted with 17 immigrant youths with intellectual disabilities aged 13-24 years and 16 caregivers, originally from Middle Eastern countries. The participants’ prioritized problems were categorized using the International Classification of Functioning, Disability and Health-Children & Youth Version, focusing on Activity and Participation. Results: A difference in priorities during transition was found when comparing the youths’ and the caregivers’ views. Most of the youths’ priorities were identified in the chapter “Major Life Area” about basic economic transactions and seeking employment, whilst the caregivers thought their youths’ prioritized “self-care”. Conclusion and implications for practice: Planning the best transition for immigrant youths with disabilities involves enabling them to identify their own preferences and needs while collaborating with caregivers and taking into consideration the cultural norms and traditions of collective caregiving.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.072
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0020.001
Open science0.0000.003
Research integrity0.0010.001
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 head0.227
GPT teacher head0.462
Teacher spread0.235 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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