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Record W4408127131 · doi:10.1177/10443894241297858

Relational Community-Based Individualized Support for Youth Who Have Experienced Homelessness: Removing Barriers to Independence

2025· article· en· W4408127131 on OpenAlexaffabout
Kathleen Manion, Jo Axe, Elizabeth Childs

Bibliographic record

VenueFamilies in Society The Journal of Contemporary Social Services · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsRoyal Roads University
Fundersnot available
KeywordsParticipatory action researchPublic relationsQualitative researchIndependence (probability theory)SociologyFoster careThrough-the-lens meteringAction (physics)Action researchPsychologyPolitical scienceNursingMedicineSocial scienceLens (geology)

Abstract

fetched live from OpenAlex

This article describes the challenges and issues associated with providing meaningful individualized support for youth who have experienced homelessness through the lens of a not-for-profit supportive employment and housing program provider based in a tourist town in Canada. This article challenges common atomistic approaches to individual support that fail to recognize the importance of the community in which they are provided and tend to underplay the vital role of relationality. Drawing on findings from a qualitatively-driven participatory action research multi-year project, this article describes a qualitative meta-analysis of findings from one organization that articulate the human needs required for optimal functioning, through the lens of Siksika wisdom, Cross’s relational worldview model, and Blackstock’s Breath of Life theory. The research findings emphasized the importance of the intersection of community, relationality, and communications to support program and participant success.

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)0.005
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 score0.018
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0030.002
Open science0.0010.008
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.073
GPT teacher head0.392
Teacher spread0.319 · 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
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueFamilies in Society The Journal of Contemporary Social ServicesSame topicHomelessness and Social IssuesFrench-language works237,207