Carlisle Indian Industrial School: Indigenous histories, memories, and reclamations
Bibliographic record
Abstract
The Carlisle Indian School (1879–1918) was an audacious educational experiment. Capt. Richard Henry Pratt, the school’s founder and first superintendent, persuaded the federal government that training Native children to accept the white man’s ways and values would be more efficient than fighting deadly battles. The result was that the last Indian war would be waged against Native children in the classroom. More than 10,500 children from virtually every Native nation in the United States were taken from their homes and transported to Pennsylvania. Carlisle provided a blueprint for the federal Indian school system that was established across the United States and served as a model for many residential schools in Canada. The Carlisle experiment initiated patterns of dislocation and rupture far deeper and more profound and enduring than its initiators ever grasped. Carlisle Indian Industrial School offers varied perspectives on the school by interweaving the voices of students’ descendants, poets, and activists with cutting-edge research by Native and non-Native scholars. These contributions reveal the continuing impact and vitality of historical and collective memory, as well as the complex and enduring legacies of a school that still touches the lives of many Native Americans.
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 | 0.001 | 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 | 0.019 | 0.014 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".