Living on the Streets in Canada: A Feminist Narrative Study of Girls and Young Women
Bibliographic record
Abstract
Homelessness affects thousands of girls and young women in Canada. Terms that are commonly used to describe the homeless include lazy, mentally ill, middle aged, and male. The reality is that homelessness is not limited to a particular age, gender, or ethnocultural group, or to individuals of any single intellectual ranking. As a result of the prevailing stereotypes, little research has been conducted on homelessness among adolescent females, making it difficult to capture an accurate and comprehensive picture of the full scope of the problem. The purposes of this feminist narrative study were to (1) explore the intersections between homelessness and health among adolescent girls, with particular attention to the influence of contextual factors such as violence, gender, and poverty; and (2) to examine how these young women access health care, barriers they encounter, and factors that contribute to their health promotion. The sample consisted of ten females, ages 16-21, who were interviewed either individually or in small groups. Consistent with feminist research approaches, the interviews were conducted in an interactive manner in order to encourage critical reflection and dialogue. Data analysis consisted of a thematic analysis of the participants' experiences. Findings revealed that most girls had fled from difficult, and at times dangerous, situations at home to lives on the street that brought a new set of challenges, including a multitude of health problems and exposure to violence, chronic poverty, and discrimination. Many barriers to effective health care were described. In this article, the findings of the research will be presented and implications for health and social service providers will be addressed, including recommendations for programming and policy.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.045 | 0.016 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| 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".