Parental responsibility for youth crime: a comparative study of legislation in four countries
Bibliographic record
Abstract
This is a comparative study of how four countries –Canada, United States of America, England and Wales, and Australia –have developed youth crime related parental responsibility laws. In particular, I explore how governments have responded to calls for making parents more responsible for the criminal behavior of their children by relying on methods of governing that seek to incorporate the concept of “responsibilization” into legislation and practice. In doing so, I show how governments in a number of countries have ostensibly moved toward less state intervention in the prevention of youth criminality and have come to rely more on parents by enacting laws that acknowledge parental accountability for the criminality of children. In addition, this study uses the concept of policy transfer to examine how those responsible for developing youth criminal justice policy look to policies or laws in other jurisdictions for ways to prevent youth criminality. Despite the fact that there are similarities in legislation across the four countries examined in this study, only minimally do governments in these countries make reference to policies found in other countries. The thesis also looks at specific national and state–level government debates surrounding parental responsibility laws, and the perceptions governments elected officials have of youth criminality and parental responsibility.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".