Reconciliation and environmental justice
Bibliographic record
Abstract
The conclusion of the Truth and Reconciliation Commission (2015) launched a new chapter in Indigenous-state relationships in Canada. Despite many resulting ‘reconciliation initiatives’, there remains considerable discussion as to what form reconciliation should take and for what end. Reconciliation processes must involve Indigenous peoples from the outset and should be founded on Indigenous intellectual and legal traditions. Indigenous peoples’ conceptions of reconciliation differ markedly from state-sponsored views, particularly the view that reconciliation must be achieved among all beings of Creation, including all living things and entities that broader society does not consider to be alive (e.g. water). Indigenous concepts of reconciliation extend discussions beyond human dimensions to encompass reconciliation with the natural world as a path forward to achieve justice. As such, reconciliation must also include discussion of Indigenous environmental justice, as both Indigenous and non-Indigenous peoples need to heal their damaged relationships with each other and to the land. The Anishinaabe concept of Mino-bimaatisiwin the ‘good life’, or ‘living well’) offers guidance for ensuring that balanced relationships among all beings of Creation are maintained. Concepts such as these could provide significant guidance as we work towards achieving a more sustainable and just society through reconciliation efforts.
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 | 0.013 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.067 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".