Street involved First Nations female adolescents’ perceptions of their futures
Bibliographic record
Abstract
First Nations youth in Canada are at a disproportionate risk of being apprehended, becoming involved in the justice system, abusing substances, being unemployed and out of school and taking their own lives. Given the conditions faced by many First Nations female adolescents, it was believed that an understanding of their future perceptions could provide the social work profession with a wealth of information relevant to their service needs. This qualitative, exploratory research explored the future outlooks of five street involved female First Nations adolescents living in Vancouver. Using an interview guide, in-depth interviews were conducted and these young women were asked to describe different aspects of lives in the future. The interviews were auto-taped, transcribed and then analyzed for common themes. It was found that these young women had strong apprehensions about ever becoming married and expressed an array of negative experiences with respect to relationships with men. They all anticipated being employed in the future in mainly traditionally female-dominated occupations. They all had desires to further their education in the future, but expressed uncertainties about how successfully they would be able to this. These young women also expressed enormous fears about their futures. They feared not making to adulthood, that drugs and alcohol would negatively effect their futures and that people close to them may die. Their future outlooks, however, also reflected great resistances towards many destructive forces in their lives. They had strong desires to maintain their family connections in the future despite revealing separation and breakdown of their families in their present lives. They also expressed longings to remain connected to their cultures and roots in the future despite the losses they had experienced. They also had strong desires to provide better lives for their own children in the future. It is recommended that social work as a profession evaluate their contemporary responses to dealing with the issues confronting these young women. Social work practice needs to incorporate community development interventions and social action which work towards altering the current inequities faced by this population.
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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 | 0.000 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".