From Blood Quantum to Liquid Gold: Black Creeks and Oklahoma’s First Resource Curse
Bibliographic record
Abstract
Abstract: This article investigates one of the most litigated and controversial court cases over Dawes enrollments in Oklahoma history from the perspective of Sally Atkins (1855–1924). Atkins, born into slavery in Missouri, married into an estelvste (African Creek) family in Indian Territory after the Civil War. Atkins migrated to Canada following statehood but was drawn back to Oklahoma by 1917. She believed her son, Tommy, to be the rightful allottee of one quarter section of the Cushing-Drumright Oilfield, the richest oilfield in the nation at the time. This claim drew Atkins into conflict with some of the most powerful oilmen in the state, who believed that another woman—a “full-blood” Muscogee—was Tommy’s mother. Who was the real mother of Tommy? State and federal officials, along with newspaper reporters, adjudicated the case based on their preconceived notions of race and “blood” in Indian Country, leading to confounding conclusions about racial categories, mineral wealth, and kinship. Many of these notions were then codified into state laws in Oklahoma. In this article, I untangle the shifting notions of bloodlines and property rights to show how the bureaucratic imperialism of the Dawes Commission fixed white supremacist notions of race for people recognized as “Black” in Indian Territory.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.044 | 0.007 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.010 | 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".