Inuit Cyberspace: The Struggle for Access for Inuit Qaujimajatuqangit
Bibliographic record
Abstract
In the field of cyberspace studies, there has been growing interest in researching the implications of cyberspace on ethnic representations and relations, a subject of particular importance for increasingly diverse societies such as Canada. In this essay, the authors examine the relationship between Internet-based new media technologies, the preservation and promotion of Inuit knowledge, and the evolution of Canada’s national identity. The authors examine whether new media technologies can serve as a means to assert and, perhaps, advance Inuit values, linguistic and cultural legacy, knowledge systems and political philosophy. The case study of the development of the Nanisiniq Inuit Qaujimajatuqangit (IQ) Adventure Website, a community-based initiative, illustrates how new media technologies support the documentation and integration of a system of cultural resources. The fully bilingual website (Inuktitut and English) guides the learner-user through an online journey about the relationship between Inuit and the land through an exploration of diverse resources, including a searchable database of elders recounting the ancient legend of Kiviuq to filmmaker John Houston. The authors assert that amplifying Inuit voices via the Internet supports new patterns of engagement between Inuit elders and youth, and among their communities. Furthermore, the case study highlights how new media technologies can “push” Inuit culture out into the world and “pull” at the national power centre that continues to ignore Northerners’ policy needs. The case study’s focus on environmental stewardship reveals how online representations of ancient knowledge systems can inspire postcolonial patterns of engagement between humans, and between humans and the environment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.050 | 0.014 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".