Young People Involved with Voluntary Youth Services Agreements in Ontario
Bibliographic record
Abstract
Abstract In 2018, significant legislative changes were made in child welfare in Ontario, Canada. As part of the changes, a Voluntary Youth Services Agreement was developed to allow young people between 16 and 17 years of age to obtain the necessary support services that they need to be able to further their independence, autonomy and agency in their lives. Yet, hearing directly from young people about the benefits and challenges of this program is limited. This study was intended to address these gaps. There were 15 young people (11 females and four males) who participated in a telephone interview about their views and experiences with the VYSA agreements. The majority spoke positively about the benefits of the programme and being able to continue their schooling, purchase clothing and obtain employment. They also believed that the programme allowed them more security and safety than being homeless. Some raised the challenges related to the amount of money that they received should be determined by the place that they reside in as some cities are more expensive than others. From a policy perspective, as the program continues, further changes may also be explored that examines the eligibility criteria where young people must be in need of protection before they can enter the program. In other words, moving from a deficit-based approach to a more child centred practice that includes hearing from young people in child welfare.
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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 | 0.001 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".