Intervisibility, Invisibility, and Identity Conflict in the Dakota–U.S. War of 1862
Bibliographic record
Abstract
This study shows how Indigenous identities, particularly of Dakota and Métis people, affected strategic choices made on the Wood Lake battlefield, and the larger Dakota–U.S. War of 1862. Before the war, people with Dakota ancestry were able to transcend rigid racial categorizations, situationally adjusting their identities to navigate changing social and political settings. As conflict with whites intensified, Dakota and Métis people were forced to materialize and project clear wartime allegiances, concealing aspects of their multi–faceted identities to align with white interests or Dakota resistance. Artifact and intervisibility analysis of the battlefield has improved our understanding the conflict, showing how Dakota people and their relations deployed invisibility, visibility, and complex group identities within asymmetrical warfare. The resulting narratives using new data can challenge simplistic dominant narratives of the war that “haunt” Mni Sota Makoce with images of racialized, disorganized, and dichotomized oppositions within the Dakota community.
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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 | 0.001 |
| 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 | 0.015 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".