If suit people are going to listen. A strengths-based perspective on Indigenous homeless youth
Bibliographic record
Abstract
Indigenous youth are overrepresented within homelessness and form approximately 20 percent of the total youth homeless population in Canada that uses emergency shelters. While extensive studies have been conducted and new practices have been put in place in an effort to reduce the number of individuals experiencing homelessness, the number of Indigenous youth journeying into homelessness continues to increase. This suggests that the solutions implemented to date have inadequately addressed the needs of Indigenous youth and the situations integral to their worlds. The purpose of this research was to explore Indigenous youths’ experiences of homelessness that promote positive identity development. It used a community-based Indigenous methodology. Building on research by Indigenous and non-Indigenous academics with the stories of Indigenous homeless youth, this research was centered at the intersection of Indigenous youth homelessness and their engagement in behaviours affected by past and present events that impact their processes of identity development. With its strengths-based lens, it deepens understandings of how Indigenous homeless youth create prosocial outcomes that bolster their self-esteem and encourage positive identity development that will support them in young adulthood and stages beyond. Indigenous youth prosocial outcomes must include holistic health outcomes that encompass spiritual, physical, mental and emotional well-being. Ultimately, this research challenges existing conversations held in society regarding Indigenous youths’ behaviours exhibited in homelessness and contributes to Indigenous resurgence, equitable colonial-Indigenous relationships, and reconciliation consistent with the goals put forth in the Truth and Reconciliation Commission of Canada’s recommendations.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.024 | 0.018 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".