Savages, Saviours and the Power of Story: The Figure of the Northern Dog in Canadian Culture
Bibliographic record
Abstract
This research was motivated by a recent pattern in animal welfare texts in Canada that portray northern dogs as “savage” trouble-makers, and indigenous people as backward barbarians incapable of caring for the animals that share their spaces. With this comes the troublesome idea that, yet again, the only positive force in indigenous Canada is the civilizing force of outsider intervention: northern dogs need to be rescued; non-indigenous people are their rightful saviours. It is a story that has been circulating in the dominant culture in Canada for centuries, and has urgent implications for both human and non-human animals in Canada’s North. \n \nThis dissertation consists of three sections. In the first section, I explore the roots of the colonial figure of the “noble canine savage” through representations in explorers’ journals, ethnographic films and tourism marketing texts. In section two, I consider how the represented dog differs in texts created within the framework of indigenous knowledge, including origin stories, indigenous cinema and elder testimony regarding the sled dog cull in Canada’s North in the mid-20th century. In section three, I return to the current media texts, and explore how they reproduce the racist rhetoric of the past. \n \nThe aim of my study was to validate the indigenous view of northern dogs in order to better incorporate local stories into animal welfare projects in northern Canada. Future interventions in this regard may include the use of cultural exchange activities between indigenous and non-indigenous partners in such projects (e.g. between local community groups and visiting veterinary teams); prioritization of narrative approaches to relationship-building; and the use of more culturally sensitive language in public relations and marketing texts.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.036 | 0.035 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.003 |
| 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".