Introduction: Exploring the Global North, from the Iron Age to the Age of Sail
Bibliographic record
Abstract
WHEN JANET ABU-LUGHOD outlined the contours of a medieval “world system” in 1989, she located most of its “circuits” in the southern hemisphere (see map 1.1). In the decades since the publication of this influential work, changing trends in research, novel approaches to evidence, and collaborative methodologies have complicated, enriched, and expanded this picture, geographically and chronologically. We now know that many more networks linked the regions of Afro-Eurasia, and long before the century of the Mongol conquests (ca. 1250–1350). It is also becoming clear that any attempt to apprehend the extent and density of these networks—see, for example, map 1.2—will be inadequate and provisional, given the pace and reach of ongoing scholarship. Even this broad hemispheric view is already too limited. For one thing, it does not allow us to follow the ancient movements of colonists from Southeast Asia into the Pacific Ocean and, thereafter, across to the islands of Polynesia—and beyond—in the first millennium of the Common Era. For another, it does not capture the short-lived or seasonal settlements of Norse voyagers on the shores of what is now Newfoundland and (perhaps) other sites along the North American coastline; nor the interactions among peoples of both hemispheres. Instead, only an inadequate, interrupted oval around the arctic indicates the documented and potential interconnectivities of the circumpolar North: the contact zone spotlighted in this special issue of The Medieval Globe . In these pages, generous scholars from a range of disciplines have joined to explore the boreal globe from the northern Iron Age (especially from the fourth century ce) to the early seventeenth century, offering fresh perspectives that cross the frontiers of regional and national historiographies, as well as conventional periodizations, in order to present new perspectives on migration, trade, material culture, technology, cultural exchange, global imaginaries and epistemologies, and the interactions of humans with their environments. The first article is a remarkable introduction to all of these phenomena. In “Contesting Marginality: The Boreal Forest of Middle Scandinavia and the Worlds Outside,” Karl-Johan Lindholm and colleagues have combined the results of their ongoing projects to propose a new narrative of historical and technological developments in inland Scandinavia—based entirely on environmental, archaeological, material, and genetic evidence.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".