Digitally Re-presenting the Colonial Archive
Bibliographic record
Abstract
The Carlisle Indian Industrial School in Carlisle, Pennsylvania, is a major site of memory for Indian nations across the United States, and for those interested in the history of colonization and American education. Lieutenant Richard Henry Pratt founded the school in 1879 to implement his vision for solving the so-called “Indian Problem” of Indigenous groups opposing westward colonial expansion. During the school’s 39 years of operation, approximately 8,000 students were taken to Carlisle in an attempt to implement Pratt’s vision of “civilizing” and assimilating them by removing them from their home communities. Once at the school, Native students were forbidden to speak their own languages, wear their traditional clothing, or practice their own customs and spiritual ways. As the flagship school in the Bureau of Indian Affairs’ education program, Carlisle served as a model for other off-reservation boarding schools across the United States and in Canada. Although Carlisle closed in 1918, other schools operated well into the 20th century. The lasting and often traumatic impact of Carlisle and the Indian boarding school movement is therefore an important part of American history that warrants continued exploration, interrogation, dissemination, and discussion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.125 | 0.028 |
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".