Controversy and Conflict: NAGPRA and the Role of Biological Anthropology in Determining Cultural Affiliation
Bibliographic record
Abstract
The primary focus of this article is to examine the concept of cultural affiliation from the perspective of biological anthropology. The concept of cultural affiliation is fundamental to federal repatriation legislation including the Native American Graves and Repatriation Act (NAGPRA). Biological anthropologists are frequently called upon to assist museums and federal agencies with making determinations of cultural affiliation of human remains and associated funerary objects and objects of cultural patrimony as required by NAGPRA. Here, we present a case study from the American Southwest as a vehicle to more closely examine the role biological anthropologists play in the implementation of NAGPRA, and how the law has created tension or conflict within the field. We also examine more closely the concept of cultural affiliation as it pertains specifically to the law's regulations detailing its implementation. As a case study, we examine the process and history leading to the publication of the Notice of Inventory Completion for the human remains and funerary objects from Chaco Culture National Historical Park. Our case study includes an administrative history and a review of the biological evidence presented in the literature. The larger implications of our case study are that in addition to varying interpretations of NAGPRA, there are indications that biological anthropology is still struggling to overcome its typological perspective on biological variation. This perspective limits the field's ability to study cultural identity – past and present .
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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 | 0.018 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.007 | 0.061 |
| Scholarly communication | 0.010 | 0.011 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.006 | 0.007 |
| 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".