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Record W4409536171 · doi:10.3390/disabilities5020039

“If I Died Tomorrow, I’d Die Knowing That My Son Is Safe, Loved by the People in Here, Well Cared for, and Happy”: Exploring Maternal Perspectives on Community Living for Their Adult Children with Intellectual and Developmental Disabilities

2025· article· en· W4409536171 on OpenAlexafffundabout
Margherita Cameranesi, Maria Baranowski, Lindsay McCombe, Kayla Kostal, Javier Mignone, Shahin Shooshtari

Bibliographic record

VenueDisabilities · 2025
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsSt.AmantUniversity of ManitobaSaint Mary's University
FundersWinnipeg Foundation
KeywordsAssisted livingGerontologySociologyGender studiesPsychologyMedicine

Abstract

fetched live from OpenAlex

There is abundant evidence that, following community transition or deinstitutionalization, persons with intellectual and developmental disabilities experience improvements in quality of life and well-being. However, very little research in this area has been conducted in the Canadian context. In this qualitative study, individual in-depth interviewing was used to explore the perspectives of eight Canadian mothers of adults with intellectual and developmental disabilities regarding their children’s residences and access to services after community transition. Within an interpretive description framework, narrative data collected during semi-structured interviews with participating mothers were analyzed using thematic analysis. Three main themes portraying a combination of positive and negative maternal perspectives emerged from the data: (1) quality of care, (2) quality of life, and (3) health status and behavior. The study findings bring attention to the importance of offering individualized community living options that are person- and family-centered to all persons with intellectual and developmental disabilities.

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)0.003
metaresearch head score (Gemma)0.005
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.877

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.007
Scholarly communication0.0020.002
Open science0.0010.002
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 head0.054
GPT teacher head0.303
Teacher spread0.250 · 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
Published2025
Admission routes3
Has abstractyes

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