1 Canada Opposes The United Nations ’ Declaration Of 2007 Recognizing The Rights Of Indigenous Peoples: Is Canada’s Strident Opposition An Anomaly Or A Symptom Of A Troubling Transformational Shift In Canadian Values?
Bibliographic record
Abstract
When most of us talk about a clash of civilizations, we think of Samuel P. Huntington‟s 1993 prophesy that the most likely pending source of cultural conflict would be between the followers of Islam and Christianity (Huntington 1993). But, with the advancement of a new era of globalization in the 1980s, another clash has re-emerged. Three hundred and seventy million indigenous people, located in over 5,000 distinct cultural communities, are required increasingly to defend their historical claims and rights against the encroaching global economic interests coveting access to their resource-rich lands. Capping 22-years of raucous debate, on September 13, 2007 the General Assembly passed the United Nations Declaration on the Rights of Indigenous Peoples. Only Canada and three other developed countries, the United States, Australia, and New Zealand remain strongly opposed to this long awaited, non-binding UN declaration. This paper examines the case for Canada‟s continued opposition to what, on its face, seems to be an anomaly in the support for cultural and human rights ‟ values long espoused by Canada; and further, if this position is not an anomaly, is it a symptom of a much deeper and more troubling transformational shift in Canadian values?
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.035 | 0.011 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.006 | 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".