Western Washington University Panel Discussion | Hidden Silence: How Does Education Shape a Nation?
Bibliographic record
Abstract
In this roundtable, speakers addressed the long-term impacts of residential and boarding schools for Native people in the U.S. and Canada. The panel included Chief Bev Sellars (Xat’sull First Nation/Soda Creek First Nation), Dr. Hollie Mackey, North Dakota State University (Northern Cheyenne), and Anna Lees Ed.D., Western Washington University (Little Traverse Bay Bands of Odawa, descendant). Drawing on their own experiences, work, and activism, the panel reflected on the effects of lasting trauma and discuss efforts of healing and rehabilitation for Indigenous communities. A blessing and land acknowledgement was delivered by Lummi Nation Elder Juanita Jefferson and Laural Ballew, Western's executive director of American Indian/Alaska Native and First Nations Relations & Tribal Liaison to the President. This panel sought to further contextualize the 2023 Joseph and Rebecca Meyerhoff Annual Lecture co-hosted by Western Washington University and the United States Holocaust Memorial Museum on Friday, April 7, 2023. More information about this discussion can be found at https://www.wwu.edu/hidden-silence.
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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 | 0.008 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.027 | 0.005 |
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".