Kinshipwrecking: John Smith’s adoption and the Pocahontas myth in settler ontologies
Bibliographic record
Abstract
John Smith’s Generall Historie of Virginia, New-England, and the Summer Isles (1624) canonized a settler colonial narrative activity that I call kinshipwrecking—a conventional mode of storytelling that destroys and moves to supplant traditional Indigenous kinship structures and obligations. Smith’s archetypal refusal of Indigenous kinship is arguably the most important element of his text, and yet it has been treated as an afterthought in most previous scholarship. His Historie depicts the process of colonization as a war between English patriarchal governance and Indigenous kinship systems—the latter of which are portrayed as power structures that must be infiltrated (through alliance or adoption) and exploited by the English and destroyed/transformed from within. The colony Smith wrote about is today remembered as the first permanent English settlement on Turtle Island, and Settlers in what some now call Canada and the USA continue to live their lives within the legacy of Smith’s archetypal and systematic rejection of Indigenous kinship. Using Mattaponi oral history as a counter narrative that both challenges and contextualizes Smith’s in/famous tale, this article considers the Settler mythology of Pocahontas and Wahunsenaca (Powhatan) through the lens of Indigenous customary or traditional adoption practices.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.023 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".