Rising Waters, Rising Threats: The Human Trafficking of Indigenous Women in the Circumpolar Region of the United States and Canada
Bibliographic record
Abstract
Among indigenous people around the world, human trafficking is taking a tremendous toll. While trafficking is not an exclusively indigenous issue, disproportionately large numbers of indigenous people, particularly women, are modern trafficking victims. In Canada, several groups concerned about human trafficking have conducted studies primarily focused on the sex trade because many sex workers are actually trafficking victims under both domestic and international legal standards. These studies found that First Nations women and youth represent between 70 and 90% of the visible sex trade in areas where the Aboriginal population is less than 10%. Very few comparable studies have been conducted in the United States, but studies in both Minnesota and Alaska found similar statistics among U.S. indigenous women. With the current interest in resource extraction, and other opportunities in the warming Arctic, people from outside regions are traveling north in growing numbers. This rise in outside interactions increases the risk that the indigenous women may be trafficked. Recent crime reports from areas that have had an influx of outsiders such as Williston, North Dakota, U.S. and Fort McMurray, Alberta, Canada, both part of the new oil boom, demonstrate the potential risks that any group faces when people with no community accountability enter an area. The combination of development in rural locations, the demographic shift of outsiders moving to the north, and the lack of close monitoring in this circumpolar area is a potential recipe for disaster for indigenous women in the region. This paper suggests that in order to protect indigenous women, countries and indigenous nations must acknowledge this risk and plan for ways to mitigate risk factors.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".