Trauma and homelessness among Indigenous people in northern Ontario: a narrative study
Bibliographic record
Abstract
Homelessness has been rising over the last 20 years. The literature outlines the need for further \nstudy of the experiences of trauma among Indigenous people who experience homelessness. \nSocial work research and front-line practice underscore the significance of trauma as a \ncontributing factor leading to homelessness. This thesis examines the narratives of an Indigenous \nman (Fred) and an Indigenous woman (Kim) who have experienced similar life events, despite \ntheir origins in geographically dispersed communities—a remote northern Cree First Nation and \nan urban centre in western Canada. The main themes emerging from an examination of their \nnarratives reveal common sets of experiences linked to Indigenous heritage. Results of narrative \nanalyses of their life stories show that both Kim and Fred experienced early childhood trauma \nleading to parallel experiences of symptoms of post-traumatic stress disorder (PTSD). Kim and \nFred both identified disconnection from their culture, oppression, early childhood trauma, \nseeking safety, substance misuse, marginalization and homelessness in their lives. These \nexperiences were compounded by seemingly cumulative effects, leading to a cycle of repeating \nadverse experiences. The results of this study indicate that social workers should focus on \neducation in rural communities to offer more strategies to prevent early childhood and ongoing \ntrauma in adulthood. The results also revealed a need for social workers to develop specialized \ntraining in substance misuse treatment that targets the reduction of and recovery from trauma \nsymptoms. The study also uncovered the need for more strategies for decolonization practices \nand solutions to overcrowding in housing in First Nations communities.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".