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Record W2604565150

Savages, Saviours and the Power of Story: The Figure of the Northern Dog in Canadian Culture

2015· dissertation· en· W2604565150 on OpenAlexaboutno aff
Maureen Elizabeth Riche

Bibliographic record

VenueYorkSpace (York University) · 2015
Typedissertation
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousEthnographyColonialismTourismPower (physics)WelfareGender studiesHistoryGeographyEthnologySociologyPolitical scienceMedia studiesAnthropologyLawEcology
DOInot available

Abstract

fetched live from OpenAlex

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.
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\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.
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\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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.408
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.271
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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