Weaving the Strands of Life (<em>Iiná Bitł'ool</em>): History of Genetic Research Involving Navajo People
Bibliographic record
Abstract
To date, some genetic studies offer medical benefits but lack a clear pathway to benefit for people from underrepresented backgrounds. Historically, Indigenous people, including the Diné (Navajo people), have raised concerns about the lack of benefits, misuse of DNA samples, lack of consultation, and ignoring of cultural and traditional ways of knowing. Shortly after the Navajo Nation Human Research Review Board was established in 1996, the Navajo Nation recognized growing concerns about genetic research, and in 2002 they established a moratorium on human genetic research studies. The moratorium effectively has protected their citizens from potential genetic research harms. Despite the placement of the moratorium, some genetic research studies have continued using blood and DNA samples from Navajo people. To understand the history of genetic research involving Navajo people, the authors conducted a literature review of genetic or genetics-related research publications that involved Navajo people, identifying 79 articles from the years 1926 to 2018. To their knowledge, no known literature review has comprehensively examined the history of genetic research in the Navajo community. This review divides the genetic research articles into the following general classifications: bacteria or virus genetics, blood and human leukocyte antigens, complex diseases, forensics, hereditary diseases, and population genetics and migration. The authors evaluated the methods reported in each article, described the number of Navajo individuals reported, recorded the academic and tribal approval statements, and noted whether the study considered Diné cultural values. Several studies focused on severe combined immunodeficiency disease, population history, neuropathy, albinism, and eye and skin disorders that affect Navajo people. The authors contextualize Diné ways of knowing related to genetics and health with Western scientific concepts to acknowledge the complex philosophy and belief system that guides Diné people and recognizes Indigenous science. They also encourage researchers to consider cultural perspectives and traditional knowledge that has the potential to create stronger conclusions and better-informed, ethical, and respectful science.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".