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Record W4406734883 · doi:10.15402/esj.v11i1.70872

Schools as Sites of Homelessness Prevention

2025· article· en· W4406734883 on OpenAlexaffvenueabout
Jayne Malenfant, Naomi Nichols

Bibliographic record

VenueEngaged Scholar Journal Community-Engaged Research Teaching and Learning · 2025
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsTrent UniversityMcGill University
Fundersnot available
KeywordsSociologyPsychologyPolitical science

Abstract

fetched live from OpenAlex

Youth homelessness in Canada impacts a significant number of young people. More specific to our focus, populations of young people who are more likely to experience homelessness (e.g. youth with mental health issues, 2SLGBTQIA+ youth, youth from care, and Indigenous youth) face significant barriers to accessing safe, culturally appropriate, and supportive education, suggesting rights to housing and rights to education are intersecting equity issues. This article presents findings from a participatory research project led by members of Youth Action Research Revolution, carried out in Tio’tiá:ke/Montréal, Québec, Canada. Building from experiences young people shared, this article highlights aspects of the public education system that pose problems for youth who are precariously housed or homeless, namely, the application of one-size-fits-all approaches, barriers for students with mental health or learning disability diagnoses, and the lack of clear or actionable institutional mechanisms for students to access preventative support. Following this, we outline educational discourses, practices, and processes that constitute where something may have been done differently to prevent homelessness. We conclude with possible actions to support youth homelessness prevention in schools, including creating more flexible ways for children and families to access supports, resourcing “champion” teachers, and addressing the insidious biases and discrimination in the organization of school policies.

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)0.817
metaresearch head score (Gemma)0.672
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.788
Threshold uncertainty score0.961

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.8170.672
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.5410.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.789
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 head0.185
GPT teacher head0.512
Teacher spread0.327 · 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; both teacher heads agree on what is shown here.

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

Explore more

Same venueEngaged Scholar Journal Community-Engaged Research Teaching and LearningSame topicHomelessness and Social IssuesFrench-language works237,207