What do repatriation and reclamation sound like? Two examples from the Hopi Cultural Preservation Office
Bibliographic record
Abstract
Abstract When the Native American Graves Protection and Repatriation Act (NAGPRA) was passed in 1990, it marked an important shift in relations between tribal communities and non‐tribal museums in the United States. By listening to how different speakers at the Hopi Cultural Preservation Office talk about repatriation and reclamation, we can see that these processes involve more than the return of ancestors and belongings; they also influence how people speak about and express group identity. In discussions about repatriation, Hopi community members frequently talk to outsiders and adjust to their ways of speaking, if only temporarily. I compare two instances in which speakers creatively used possessive constructions to convey different scales of identity and argue that Bakhtin's concept of “addressivity” illuminates connections between the two. More broadly, I suggest that this concept is useful for thinking about how relationships between tribal and non‐tribal institutions might continue to be transformed in ways that are responsive to contemporary Indigenous claims and presence.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.029 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".