Assessing the Impact of Water Insecurity on Maternal Mental Health at Six Nations of the Grand River
Bibliographic record
Abstract
The Haudenosaunee or Six Nations (SN) is a matrilineal society sustained through reciprocal relationships with nature and all creation. Haudenosaunee hold a special relationship and responsibility with water, as it is the first environment of humans. Colonialism attacked Haudenosaunee land, women, children, and traditional ways of life. The Haudenosaunee were displaced from their land and were forced to migrate to a reserve. Colonial and capitalist agendas contaminated water leaving the Six Nations, Canada's most populated reserve, without clean running water and making SN women and children more vulnerable to water insecurity. The Ohneganos, an SN community project, is intersectional, and the intersectionality of health, culture and water identified maternal health as understudied in water insecurity research. Research on Indigenous mental health mainly focused on suicide and substance abuse and ignored the root causes of violent colonial structures and policies such as the Indian Act and residential schools. Our research suggests that gender, migration and water for Indigenous communities must be contextualized with larger violent colonial structures such as environmental racism and epistemic violence. Ohneganos research examines impacts of water insecurity on maternal health and co-developed design and implementation with Six Nations Birthing Center (SNBC). The SNBC's traditional Haudenosaunee health care practices shaped the research, revealing the critical importance of community-led research's efficacy. Haudenosaunee and anthropological research methods are employed to assess the impact of water insecurity on maternal mental health. The co-designed semi-structured interviews highlight the voices of 54 participants consisting of mothers (n= 41), grandparents (n= 10), and midwives (n= 3) of SN. Most participants expressed that the lack of clean water had profound impacts on mental health and had recurring thoughts about the lack of clean water in the SN community. Mental health issues, including depression and anxiety, were reported due to a lack of running water. Despite experiencing water insecurity, Haudenosaunee women demonstrate resiliency through culturally innovative adaptations to their changing environment.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".