Female Veterans’ risk factors for homelessness: A scoping review
Bibliographic record
Abstract
Introduction: The proportion of Canadian female Veterans who are homeless is greater than that of their male counterparts. The Standing Committee on Veterans Affairs recommended research be conducted to better understand Canadian female Veteran homelessness. In response to this recommendation, this scoping review of peer-reviewed literature and grey literature was undertaken as a first step to identify the existing literature exploring homelessness among female Veterans. Methods: A scoping review of the literature was performed, focusing on the risk factors and lived experiences associated with homelessness among female Veterans. Articles were screened for relevance and critically appraised. Results: A total of 927 studies were retrieved. Nine articles were added from additional sources. After a two-phase screening approach, 15 studies were included for analysis. All studies were from the United States. Several risk factors for homelessness were identified for female Veterans across their lifespan: adverse childhood events, abuse, family upheaval, military sexual trauma, intimate partner violence, substance use, physical and mental health diagnoses, race and racism, and gender discrimination. Discussion: This scoping review illustrates that a paucity of literature exists on the life experiences of Canadian female Veterans who are homeless. However, it identified several important themes that can guide future research focused on understanding the risk factors contributing to homelessness for this population. Furthermore, a critical analysis of existing literature illustrated the need for research focused on the interactions among social location, historical experience, and socio-demographic characteristics to more fully understand the risk factors that influence being homeless.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".