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Record W4402405598 · doi:10.23889/ijpds.v9i5.2697

Using linked administrative data to describe a cohort of young people who have a parent with a history of homelessness (Study 1)

2024· article· en· W4402405598 on OpenAlexaffabout
Jino Distasio, Aynslie Hinds, Corinne Isaak, Jaime Cidro, Nathan Nickel, Sarah Zell, Jitender Sareen

Bibliographic record

VenueInternational Journal for Population Data Science · 2024
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsCohortPsychologyDemographyGerontologyDevelopmental psychologySociologyMedicine

Abstract

fetched live from OpenAlex

ObjectiveLittle is known about the children of parents who experience homelessness. The At Home/Chez Soi (AHCS) Research Demonstration Project, launched in 2009, was a Canadian multi-site, multi-year study that tested the effectiveness of Housing First. In Winnipeg, 513 people were enrolled, of whom 47% were parents. Our objective was to determine how the children were faring with respect to their health and social situations at a time their parent was experiencing homelessness. ApproachThe cohort, created using the Manitoba Centre for Health Policy’s familial linkage methodology, consisted of 405 individuals (< 30 years old) who were the offspring of the Winnipeg AHCS cohort. We descriptively summarized the socioeconomic characteristics and indicators of their involvement (or lack thereof) in various government systems at or in a period up to their parent’s study enrolment date. ResultsApproximately half of the cohort were female (51%) and under 13 years (52%). Most (76%) resided in a household that had received income assistance. At least 50% had been placed into care at or near birth and only 17% had not been involved with the child welfare system. Of those school aged, 81% were enrolled in school and of those older than school aged, 53% had graduated. Nearly half (49%) had been diagnosed with a mental health disorder and/or with asthma (47%). Conclusions and ImplicationsThis study is the first in a series seeking to identify ways to prevent multigenerational experiences of homelessness. Findings will generate valuable insights for upstream intervention across various systems.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.087
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0020.001
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 head0.364
GPT teacher head0.530
Teacher spread0.166 · 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 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

Citations0
Published2024
Admission routes2
Has abstractyes

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