MétaCan
Menu
Back to cohort
Record W4384377104 · doi:10.36251/josi41

Homeless university students: Experiences with foyer-type service

2012· article· en· W4384377104 on OpenAlexaff
Marty Grace, Deborah Keys, Aaron Hart

Bibliographic record

VenueJournal of Social Inclusion · 2012
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAccommodationDuration (music)Service (business)RefugeeSociologyMedical educationPsychologyMedicinePolitical scienceBusinessMarketing

Abstract

fetched live from OpenAlex

Some young people who have been homeless during their secondary schooling manage to obtain a university place. These young people, and others who become homeless during their university courses, have the opportunity to build a sustainable exit from homelessness through education and support. Very little is known about how many young Australians are in this situation, or what can be done to assist them to complete their degrees. This article reports on research that aimed to document the experiences of 11 university students who had experienced homelessness. The research focussed on the difficulties that these young people faced, and the types of environments and service responses that can make a difference for them. The students were part of a larger study of a foyer-type service. The research found that these young people took longer than the standard duration to complete their degrees. Their study was facilitated by provision of stable, safe accommodation and support when they were acutely homeless, relief from other pressures such as family conflict, protection while maturing, time for overseas born including refugee young people to develop language, skills, and resources, support to heal from past damaging experiences and improve their health, assistance to gain entry to preferred university courses, and pathways into stable housing for the duration of their study.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.074
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0030.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.041
GPT teacher head0.409
Teacher spread0.367 · 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.

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

Citations2
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Social InclusionSame topicHomelessness and Social IssuesFrench-language works237,207