Human Trafficking in Northeastern Ontario: Collaborative Responses
Bibliographic record
Abstract
Human trafficking for the purpose of sexual exploitation is undoubtedly occurring in Northeastern Ontario. However, there is a lack of information, resources, coordination, and collaboration on the issue in comparison to Southern Ontario. Furthermore, urban-based programming from “down south” does not necessarily fit the unique circumstances of Northeastern Ontario: specifically, the isolation and underservicing of rural and remote communities, the presence of francophone communities, and diverse Indigenous communities. The Northeastern Ontario Research Alliance on Human Trafficking is a community-university research partnership that takes a critical anti-human-trafficking approach. We combine Indigenous and feminist methodologies with participatory action research. In this paper, we first present findings from our eight participatory action research workshops with persons with lived experience and service providers in the region, where participants identified the needs of trafficked women and gaps and barriers to service provision. Second, in response to participants’ calls for collaboration, we have developed a Service Mapping Toolkit that is grounded in Indigenous cultural practices and teachings, where applicable, and in the agency and self-determination of persons experiencing violence, exploitation, or abuse in the sex trade. We conclude by recommending seven principles for building collaborative networks aimed at addressing violence in the sex trade. The Service Mapping Toolkit and collaborative principles may assist other rural or northern communities across the county.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.007 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.002 |
| 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".