Gardening in Ashes: The Possibilities and Limitations of Gardening to Support Indigenous Health and Well-Being in the Context of Wildfires and Colonialism
Bibliographic record
Abstract
In this paper, we will discuss gardening as a relationship with nature and an ongoing process to support Indigenous health and well-being in the context of the climate crisis and increasingly widespread forest fires. We will explore the concept of gardening as both a Euro-Western agriculture practice and as a longstanding Indigenous practice-wherein naturally occurring gardens are tended in relationship and related to a wider engagement with the natural world - and the influences of colonialism and climate change on both. Drawing on our experiences as an Indigenous Knowledge Keeper (Dancing Water) and a non-Indigenous community-based researcher (Kelsey), our dialogue will outline ways to support health and well-being through land-based activities that connect with Indigenous traditions in ways that draw on relationships to confront colonialism and the influences of climate change. This dialogue is founded on our experiences in the central interior of British Columbia, Canada, one of the areas hit hardest by the 2017 wildfires. We will explore the possibilities and limitations of gardening and the wider concept of reciprocity and relationship as a means to support food security, food sovereignty, and health for Indigenous Peoples.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.012 | 0.016 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".