Inuit Art as Cultural Diplomacy between Canada and India \nSanaugavut: Inuit Art from the Canadian Arctic
Bibliographic record
Abstract
ABSTRACT \nInuit Art as Cultural Diplomacy between Canada and India \nSanaugavut: Inuit Art from the Canadian Arctic \nOn the 27th of September, 2010 an exhibition of Inuit Art entitled Sanaugavut: Inuit Art from the Canadian Arctic, organized by the National Gallery of Canada, opened at the National Museum of India. Canada gained visibility with the Indian public as well as an international audience as the inauguration of Sanaugavut coincided with the opening of the Commonwealth Games in India. \nAn exploration of Sanaugavut contributes to the understanding of the way that Inuit art, as an artform and through the medium of exhibition, has been used by the Canadian government in furthering political and economic aspirations. The focus of this thesis then, is the study of the use of Inuit art in cultural diplomacy internationally and specifically in the case of Sanaugavut, between Canada and India. \nCultural diplomacy can be defined as an opportunity to foster mutual understanding by presenting cultural knowledge and furthering an understanding of a nation. The opportunity is the essence of the ‘soft power’ of an exhibition - its ability to present the mood of the country, providing an awareness of the characteristics of its societies and a landscape in which its politics operate. Sanaugavut, as an example of soft-power, was used as a tool in the promotion of Canada’s nationhood.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.033 | 0.009 |
| Scholarly communication | 0.011 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 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".