Bibliographic record
Abstract
The essays in this volume provide a comprehensive overview of Atlantic history from c.1450 to c.1850, offering a wide-ranging and authoritative account of the movement of people, plants, pathogens, products, and cultural practices-to mention some of the key agents--around and within the Atlantic basin. As a result of these movements, new peoples, economies, societies, polities, and cultures arose in the lands and islands touched by the Atlantic Ocean, while others were destroyed. The team of scholars in this volume seek to describe, explain, and, occasionally, challenge conventional wisdom concerning these path-breaking developments. They demonstrate connections, explore contrasts, and probe themes. During the four centuries encompassed by this collection, pan-Atlantic webs of association emerged that progressively linked people, objects, and beliefs across and within the region. Events in one corner of the Atlantic world had effects, reverberations thousands of miles away. The great virtue of thinking in Atlantic terms is that it encourages broad perspectives, unexpected comparisons, trans-national orientations, and expanded horizons; the parochialism that characterizes so much history writing and instruction today, as in the past, has a chance of being overcome. Contributors to this volume - Ida Altman, University of Florida David Armitage, Harvard University Lauren Benton, New York University Christopher Leslie Brown, Columbia University Nicholas Canny, National University of Ireland, Galway Joyce Chaplin, Harvard University Matthew Edney, University of Southern Maine David Eltis, Emory University David Geggus, University of Florida Ira D. Gruber, Rice University David Hancock, University of Michigan Tamar Herzog, Stanford University Richard L. Kagan, Johns Hopkins University Wim Klooster, Clark University Robin Law, Stirling University John R. McNeill, Georgetown University Elizabeth Mancke, Akron University Sylvia Marzagalli, University of Nice Laura de Mello e Souza, Universidade de Sao Paulo Kenneth Mills, University of Toronto Philip Morgan, Johns Hopkins University Craig Muldrew, Cambridge University David Northrup, Boston College, William O'Reilly, Cambridge University Anthony Pagden, University of California, Los Angeles Susan Scott Parrish, University of Michigan Joao Jose Reis, Universidade Federal da Bahia Daniel K. Richter, University of Pennsylvania N.A.M. Rodger, Oxford University Jaime E. Rodriguez O, University of California, Irvine Emma Rothschild, Harvard University Joan-Pau Rubies, London School of Economics John Russell-Wood, Johns Hopkins University Jean-Frederic Schaub, Ecole des Hautes Etudes en Sciences Sociales, Paris Stuart Schwartz, Yale University Carole Shammas, University of Southern California David Shields, University of South Carolina Kevin Terraciano, University of California, Los Angeles Troy L. Thompson, University of Pennsylvania Neil Whitehead, University of Wisconsin
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.010 |
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".