Bibliographic record
Abstract
Growing mainstream awareness of tensions surrounding Indigenous rights and recent political movement to promote reconciliation suggest that the time might be ripe to revisit some of the most important ideas for strengthening Indigenous Peoples’ place and space within the Canadian federation, particularly within the country’s central political institutions. This article argues that the Canadian Senate has the potential to be an important institution for reconciliation in Canada’s system of federalism. It centres on one of the proposed recommendations of the Charlottetown Accord—reserved representation for Aboriginal people in the Senate. Using a theoretical framework based in treaty federalism, this article argues that reserved Indigenous representation in the Canadian Senate could provide a starting point to mitigate some of the existing tensions between dominant understandings of federalism and reconciliation, as well as to ensure that Canada’s political institutions better represent the interests of Indigenous Peoples and Nations. The Senate’s essential responsibilities in Canadian democracy, including representing sectional interests and reviewing legislation, make it an ideal starting place for realizing commitments to reconciliation in Canada’s central political institutions.
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 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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.043 | 0.029 |
| Scholarly communication | 0.014 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 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".