Storytelling through Fire: The Socio-Ecological and Cultural Reclamation of Indigenous Cultural Fire in Northern California
Bibliographic record
Abstract
Indigenous peoples and the roles we play in mitigating climate change are necessary in public education and discourse. Climate change itself is inherently tied to colonial practices, both historically and in the present, as anthropogenic activities have hinged on the dispossession of Indigenous land and resources. Tribes throughout the state of California are actively mitigating the effects of climate change and colonialism with innovative strategies and Traditional Ecological Knowledge and practices. Since time immemorial, Tribes have always conducted cultural fires, as a spiritual and ecological approach to tending and caring for our lands. These low temperature burns not only improve the ecosystem, they also provide socio-cultural medicine which activates community healing and strengthens the intergenerational bonds between Tribal members. In California during the 1800s, government agencies began suppressing and outlawing the use of traditional cultural fire. Without traditional stewardship, including cultural fire, the appearance of the California landscape has shifted tremendously and is now susceptible to prolonged drought seasons and catastrophic wildfire. The Patwin [Southern Wintun] peoples have had success in holding community cultural fire demonstrations. These practices, held in partnership with the Tending and Gathering Garden located within the Cache Creek Nature Preserve (Woodland, CA) contextualizes the socio-cultural and ecological importance of cultural fire with Indigenous sovereign Nations in Northern California. This dissertation weaves together Ecology and Environmental Science with Native American Studies (NAS) and seeks to address critical questions on environmental stewardship, Indigenous socio-ecological healing, and Indigenous climate action. By applying diverse theoretical applications, I seek to center Indigenous knowledges by prioritizing the following developed framework rooted in NAS methodologies: relationality (relationships to the land, more-than-human Relatives, and to past and future Ancestors); reciprocity (connectedness that positions individuals in sets of relationships with each other and with the environment); re-membering (collective and individual connection of bodies with place and experience); and futurity (intergenerational exchanges, and Tribal coalition building). Further, the cross-cultural collaborations developed between Traditional practitioners, sovereign Tribal Nations, government entities, and universities provide opportunities to develop a deeper understanding of Indigenous land stewardship and can lay the groundwork for Indigenous peoples to reclaim our Ancestral lands.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".