Kids, crime, and coercion: child labour and exploitation in Nova Scotia's illegal economy
Bibliographic record
Abstract
This thesis is a preliminary study to demonstrate that some children in Nova Scotia are exploited by adults in illegal, underground markets in Nova Scotia. Children and youth are exploited in these underground economies in a manner similar to child labour in the formal sector. This use of children under the age of 19 in illegal trades in Canada has not been documented. This thesis has two main purposes. First, it provides a critical analysis of theories of child labour, the bourgeois child, and exploitation, to explain the child labour situation as it relates to illegal Canadian markets. Literature on the precise subject is scarce and this thesis uses a variety of sources on child labour generally and youth crime from Canada and abroad that helps to develop understanding of this social problem. Second, this thesis provides the results of a preliminary investigation into the problem of child labour in illegal, underground markets in Nova Scotia through an analysis of six interviews with experts in the field of youth crime, including three local police officers, a police expert on organized crime in Winnipeg, one social worker from Halifax, and a former member of the sex trade. Findings revealed that children are particularly vulnerable to exploitation, especially those in marginal situations. Juvenile prostitution, underage stripping, theft, and drug trafficking are the most common forms of illegal child labour in the province. Participants for this study revealed that this is a problem that requires further consideration. This is a topic that has received little attention, and additional research is needed so that an effective initiative may be undertaken to combat this form of exploitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| 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".