Bibliographic record
Abstract
The Red Atlantic is a concept by scholars in Native American history and Native American and Indigenous studies (NAIS) to address one of the perennial issues facing the study of the Atlantic world: the exclusion of the Indigenous Peoples of North America. In many years of existence, Atlantic world studies has focused on the movement of peoples (immigrants, slaves), goods (trade, food, diseases, etc.), and empires across the Atlantic Ocean, but rarely do such works engage with how Indigenous Americans contributed to, negotiated, and at times dictated transatlantic movements and connections. Instead, Indigenous Americans remain obstacles of empire, faceless suppliers of transatlantic goods like deerskins, peripheral figures who occupied the fringes of the Atlantic world, or proverbial boogeymen to transatlantic migrants (i.e., invaders) who settled in North America. However, as scholars of the Red Atlantic have articulated, our understandings of the Atlantic world—whether about merchant networks in New England and the West Indies or Spanish missions in Mesoamerica and Florida—are limited and altogether incomplete if Indigenous Peoples are relegated to the margins of the Atlantic world. In fact, there is much that scholars can learn from the Red Atlantic. For instance, groups like the Wabanaki were maritime people, like their European and African counterparts, as their everyday lives and cultures revolved around interactions with the Atlantic Ocean, such as enfolding European merchant networks into their own economies or turning to piracy to combat imperial expansion in their territories. Meanwhile, scholars of the Red Atlantic have brought to life the Indian slave trade in 17th- and 18th-century New France, between French and Algonquian peoples who carved out a traffic in human beings that connected Canada to France, the West Indies, and Africa, before the wholesale importation of African peoples. Indigenous American languages and local knowledge also shaped how European natural scientists came to understand foreign places, flora, and fauna, as Europeans proved dependent on Native knowledge systems to gain a better understanding of the world around them. In so many instances like these, the Red Atlantic demonstrates how to broaden interpretations of the Atlantic world paradigm and how to provide a more inclusive, holistic understanding of history. What follows is a sample of some of the most important works that have spurred or contributed to the Red Atlantic and concludes with those that have most recently nuanced, complicated, or redirected Atlantic world studies.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.393 | 0.221 |
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".