What does Truth and Reconciliation teach us about degrowth in settler societies? An exploration of the interconnections between degrowth and the TRC calls to action
Bibliographic record
Abstract
Degrowth offers pathways to stay within ecological limits while increasing human and planetary wellbeing. As settler scholars living in so-called Canada, we see a gap in the degrowth branch of ecological economics regarding degrowth transitions within settler societies, as much of this literature comes out of a European context. In this paper, we attempt to analyze the Calls to Action from the Truth and Reconciliation Commission of Canada (TRC) and the United Nations Declaration on the Rights of Indigenous Peoples, to explore how a degrowth transition may help us move forward together on the path to Reconciliation with (and decolonization of) First Nations, Metis and Inuit Peoples. We do this by reviewing relevant academic and grey literature, showing the interconnections between degrowth’s emphasis on ecological limits and reconciliation with the Land; on autonomy and Indigenous sovereignty; and on moving towards a multiplicity of knowledges to live ‘the good life’. Here, we offer an exploration of these interconnections to open up three lines of inquiry. We explore how we might ground degrowth transitions in reconciliation with Indigenous Peoples and the Land, question what degrowth means on occupied Land, and move towards pluralistic and decolonial degrowth imaginaries. We put forward this contribution to the ecological economics and degrowth communities as a challenge to engage with and act upon the Calls to Action from the TRC, and their implications for degrowth.
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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 | 0.016 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.020 | 0.109 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.004 | 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".