How Expansive Is Oregon Trail History? with Professor Margaret Huettl
Bibliographic record
Abstract
Can you map out the Oregon Trail? If you just flashed back to playing The Oregon Trail video game in your sixth grade computer lab, get ready for a journey. Jonathan and Professor Margaret Huettl explore how Native knowledge systems established the Oregon Trail; how Native peoples experienced non-Native settlers moving West; and how Indigenous communities today are reckoning with this past to build a better future. Margaret Huettl, a descendant of Lac Courte Oreilles Ojibweg, Assyrian refugees, and European settlers, is Assistant Professor in History and Ethnic Studies at the University of Nebraska-Lincoln. She is a scholar of Native American history and North American Wests, and her research examines the continuities of Ojibwe sovereignty in the context of settler colonialism in both the United States and Canada, centering Ojibwe ways of knowing. You can follow her on Twitter @historianhuettl. Want to learn more about the Oregon Trail? See whose land you're living on, or learn more about the Native nations whose land was crossed by the Oregon Trail: Native-Land.ca Visit the only Oregon Trail museum run by Indigenous people: TAMÁSTSLIKT CULTURAL INSTITUTE Explore the Fort Laramie Treaty through an interactive case study: Fort Laramie Treaty Case Study Read Margaret's work: \\"Treaty Stories: Reclaiming the Unbroken History of Lac Courte Oreilles Ojibwe Sovereignty\\" Learn more about Indigenous representations: IllumiNative. Check out some Indigenous-centered games: When Rivers Were TrailsInvadersGrowing Up OjibweNever Alone Find out what today's guest and former guests are up to by following us on Instagram and Twitter @CuriousWithJVN. Transcripts for each episode are available at JonathanVanNess.com.Check out Getting Curious merch at PodSwag.com.Listen to more music from Quiñ by heading over to TheQuinCat.com.Jonathan is on Instagram and Twitter @JVN and @Jonathan.Vanness on Facebook.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.775 | 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; both teacher heads agree on what is shown here.
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".