Northern Housing Networks: Building Collaborative Efforts to Address Housing and Homelessness in Remote Canadian Aboriginal Communities in the Context of Rapid Economic Change
Bibliographic record
Abstract
Canada's northern and remote regions experience unique challenges related to housing and homelessness. As such, there is a need to understand and develop strategies to address housing-related concerns in the North. The diversity of communities across the North demands the tailoring of specific, local-level responses to meet diverse needs. Over the past decade local networks have emerged as a powerful method for governance and development of localized responses to addressing homelessness across Canada and North America. Despite this, there is a paucity of research examining challenges and effective approaches utilized by these local networks or their potential applicability for building housing security in rural, remote, and northern communities. This research examined the experiences of a Northern Canadian housing and homelessness network. The experience of this network points to strategies that can lead to successful collaborative approaches aimed at implementing programs to address homelessness in northern and remote communities. Keywords: homelessness, collaboration, network, remote, Aboriginal ------------------------------------------------------ Le nord du Canada et les regions eloignees font face a des defis particuliers en termes de logement et d'itinerance. Ainsi, Il est necessaire de comprendre et de developper des strategies pour resoudre les problemes souleves par le logement dans le Nord. La diversite des communautes a travers le Nord demande un ajustement a des besoins specifiques, locaux et a differents niveaux, afin de repondre aux attentes variees. Au cours des dix dernieres annees, les reseaux locaux sont apparus comme des methodes de gouvernance et de developpement de reponses localisees en matiere d'itinerance a travers le Canada et en Amerique du Nord. Malgre cela, il y a un manque de recherche examinant les defis et les approches efficaces utilisees par ces reseaux locaux ou leur applicabilite potentielle pour construire des logements securitaires dans des communautes rurales, eloignees ou du Nord. Cette recherche examine les experiences d'un reseau de logement et d'itinerance canadien du Nord. L'experience de ce reseau met en valeur les strategies qui peuvent mener a des approches collaboratives reussies menant a l'implantation de programmes a l'attention des itinerants dans le nord et les communautes eloignees.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".