We Are Still Here: Frank Speck and the Continuing Presence of American Indians in the Eastern Woodlands
Bibliographic record
Abstract
This thesis will argue the importance of Speck as a scholar who forged his own path. He was a precursor to the more politically inclined anthropologists today. Speck not only studied American Indians, he advocated for them politically and legally as well as thought their then- present lives were worthy of note, too. Not all Boas trained anthropologists felt this way. Recording the traditional cultures of the tribal nations was more paramount to them. To illustrate this, I analyzed two of Speck’s largest collections, the Cherokee collection and Innu (Naskapi/Montagnais) collection, at the Penn Museum along with his papers held at the museum’s archives and the library of the American Philosophical Society. I will also review one of his earliest works, The Nanticoke Community of Delaware (1915) to learn his method then compare and contrast him to other collectors and anthropologists working at the same time, George Heye and Alfred Kroeber, respectively. Speck’s advocacy work was a precursor to the more politically inclined anthropologists of today. He helped the Six Nations at Grand River, Ontario secure stolen wampum belts. While many anthropologists studied the Indigenous west of the Mississippi River Speck stayed in the eastern half of the United States and Canada to research the tribal nations. Through the Cherokee, Innu, and Nanticoke collections one can see his nonjudgmental attitude and how much respect Frank Speck had for the Indigenous as well as his work to help tribal nations gain recognition and get stolen property back. This is why Speck is an important anthropologist to study
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.021 | 0.019 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".