Decolonizing environmentalism: Addressing ecological and Indigenous colonization through arts-based communication
Bibliographic record
Abstract
This article seeks to advance connecting the two societal priorities of environmental protection and what has been called ‘Indigenous reconciliation’ through arts-based communication (and particularly arts-based research), to help engage and inspire people towards sustaining a healthy planet and a just society. Through lenses of social justice, decolonizing critique and holistic environmental ideologies, this work explores theoretical and practical, real-world intersections of environmentalist, Indigenous and arts-based imperatives and ways of knowing. The goal is twofold: first, to seek to engage readers in viewing the colonization of the planet and its First Peoples as intimately related, and ultimately, to bring together diverse literatures to suggest ideas, language and a model to foster communication aimed at redressing both of those colonialist evils. To acknowledge this intersection of environmental and Indigenous approaches in arts-based settings, the term ‘environmental conciliation’ is proposed and defined as ‘environmental protection in ways that acknowledge, address, and aim to redress imbalances in power among Indigenous people and non-Indigenous settlers honestly, respectfully, openly, creatively and positively.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.043 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".