“We Live in a Very Toxic World”: Changing Environmental Landscapes and Indigenous Food Sovereignty
Bibliographic record
Abstract
The purpose of this article is to understand how historical oppression has undermined health through environmental injustices that have given rise to food insecurity. Specifically, the article examines ways in which settler colonialism has transformed and contaminated the land itself, impacting the availability and quality of food and the overall health of Indigenous peoples. Food security and environmental justice for Gulf Coast, state-recognized tribes has been infrequently explored. These tribes lack federal recognition and have limited access to recourse and supplemental resources as a result. This research fills an important gap in the literature through exploring the intersection of environmental justice and food insecurity issues for this population. Partnering with a community-advisory board and using a qualitative descriptive methodology, 31 Gulf Coast Indigenous women participated in semi-structured interviews about their healthcare experiences and concerns. Through these interviews, participants expressed concerns about (a) the environmental impacts of pollution on the contamination of food and on the health of tribal members; and (b) the impact of these changes on the land, such as negatively impacting gardening practices. The authors of this study document how environmental changes have compounded these concerns and contribute to the overall pollution of food and water sources and unviability of subsistence practices, severely effecting tribal members’ health. In conclusion, we show how social and environmental justice issues such as pollution, industry exploitation, and climate change perpetuate the goals of settler colonialism through undermining cultural practices and the overall health of Indigenous peoples.
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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 | 0.003 | 0.003 |
| 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 | 0.028 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".