"The Sea of trouble we are Swimming in": People of the Dawnland and the Enduring Pursuit of a Native Atlantic World
Bibliographic record
Abstract
This dissertation explores the active engagement of an American Indian culture with the early modern Atlantic world. It argues that the Wabanaki of the American northeast were a quintessentially maritime-oriented people who time and again looked to the Atlantic as an essential means of mitigating the quotidian rigors of their society and enhancing its overall welfare. This process had sustained native life long before the arrival of Europeans, and afforded it valuable cultural and material resources to assuage the disruptive effects of colonialism from the early sixteenth through the mid-eighteenth centuries. In their exchanges with Euro-Americans, these people increasingly cultivated an array of novel Atlantic opportunities to enrich, augment, and protect their vision of this pelagic world in the face of increasing pressures to redefine its meaning and significance. By shrewdly engaging in trans-Atlantic gift-giving networks, astutely exploiting European imperial conflicts, carefully manipulating economic exchange complexes, respectfully invoking European monarchical authority, and strategically appropriating Euro-American sailing technology, Wabanaki consistently reinforced their presence on the high seas and elaborated their longstanding notion of the Atlantic world: the ocean was a profoundly generative and life-sustaining locus of power.
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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 | 0.001 |
| Science and technology studies | 0.023 | 0.016 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.004 |
| 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".