Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Natural resource-based projects represent an important sector in Canada’s economy, where the energy, mining, and forestry industries accounted for 17% of Canada’s gross domestic product in 2018 (Natural Resources Canada, 2019). Many projects are located on or near Indigenous lands, disproportionately impacting Indigenous peoples (Gibson et al., 2017). The negative environmental impacts of resource-based projects are well documented (Koutouki et al., 2018; Westman & Joly, 2019); however, the social consequences are often overlooked. Recently, numerous non-profit organizations have documented a connection between resource-based projects and increased numbers of violent offences against Indigenous women (Amnesty International, 2016b; Bond & Quinlan, 2018; Pauktuutit Inuit Women of Canada, 2021;), but few academic articles have addressed this issue. Therefore, a non-systematic scoping review was conducted on available grey literature, news articles, and academic literature to examine key concepts and themes. This review demonstrates that colonization has placed Indigenous women in Canada at higher risk of violence. The introduction of resource-based projects exacerbates this issue through three key processes: the presence of “man camps,” economic changes, and changing family dynamics. In combination with an inadequate criminal justice system, the resulting violence against Indigenous women can be categorized into three overlapping groups: domestic violence, workplace violence, and sexual violence. An economic map was developed to illustrate the locations of resource-based projects associated with this issue (see Figure 1). This paper suggests potential solutions including addressing toxic workplace culture, updating policies and protocols, ensuring meaningful consultation with Indigenous peoples, and increasing government protections.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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 it