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Record W1506235007

Experiences of being homeless or at risk of being homeless among Canadian youths.

2004· article· en· W1506235007 on OpenAlexaffabout
Pamela C. Miller, Peter Donahue, Dave Este, Marvin Hofer

Bibliographic record

VenuePubMed · 2004
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDiversity (politics)Ethnic groupImmigrationService providerCultural diversityPsychologyPopulationQualitative researchSocial workSociologyService (business)GerontologyGeographyMedicineDemographyPolitical scienceSocial science
DOInot available

Abstract

fetched live from OpenAlex

A qualitative study was undertaken with four groups--immigrants, youths, Aboriginal people, and landlords--in order to explore, compare, and contrast diversity issues among the homeless population and those at risk of homelessness in a larger Canadian city (Calgary, Alberta) with a smaller city (Lethbridge, Alberta), to better understand their and to needs make recommendations for improvement in service delivery and policy formation. This paper focuses on the findings from our sample of youths who shared information on a range of factors that contributed to their being homeless or at risk of being homeless. The youths in this study also shared their positive as well as negative experiences with educators, peers, family members, and social service providers. Canada's homeless include growing numbers of young people, families, women, and members of various ethnic communities, including Aboriginal people and immigrants. Today it is no longer possible to articulate a single silhouette of the homeless, but rather a diversity of profiles is needed. It was in the light of this reality that a study, "Diversity Among the Homeless and Those At Risk," was carried out. It was undertaken with four groups--immigrants, youths, Aboriginal people, and landlords.

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)0.000
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 score0.442
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.036
GPT teacher head0.318
Teacher spread0.282 · 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

Citations34
Published2004
Admission routes2
Has abstractyes

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