Higher Education Concerns for Natives in the Post-Crisis Period
Bibliographic record
Abstract
The higher education and academic research sectors of the Canadian education sector were victims of the 2008 global crisis. Those institutions that were relying on private funding suffered from crashing values of their endowments amidst a declining market. With shrinking government budget and the universities finding tough time in the higher education and research sector, the aboriginals of Canada would be at the most disadvantageous position with respective to their economic development, since education is a central pillar to what Amartya Sen calls “entitlements and capabilities” of a community, particularly when colonialism left aboriginal peoples among the poorest of Canadians. The higher education sector of India is cited as a similar case here. This chapter examines the impact of declining funding both from private and government sources and other adversaries to the access of the aboriginals to education and thus attempts to bring to light how many educational opportunities are available to the natives in the post-crisis period in a comparative tone with India.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".