Misinformation Nation: Foreign News and the Politics of Truth in Revolutionary America by Jordan E. Taylor (review)
Bibliographic record
Abstract
Reviewed by: Misinformation Nation: Foreign News and the Politics of Truth in Revolutionary America by Jordan E. Taylor Helena Yoo Roth (bio) Keywords American Revolution, Newspapers, Communication, Media, Information, Propaganda Misinformation Nation: Foreign News and the Politics of Truth in Revolutionary America. By Jordan E. Taylor. ( Baltimore: Johns Hopkins University Press, 2022. Pp. 271. Cloth, $40.00.) Misinformation Nation follows the ebbs and flows of transatlantic communication, starting with the imperial crisis of the 1760s, continuing through the American Revolution and the turbulent years of the early republic, and concluding with the 1798 Sedition Act. With an eye for detail and a flair for narrative, Jordan E. Taylor explores how foreign news spread throughout colonial America and the early United States. Taylor builds his book around the subject of citations, a choice that that should warm every historian's heart. He has plumbed the depths of Readex's America's Historical Newspapers to create a database of over 40,000 direct citations to foreign newspapers and news sources in colonial and early republic newspapers. (For the Canadian newspapers, he used microfilm collections.) In Taylor's hands, these mundane citations "disclose a dynamic world in which war, politics, diplomacy, commerce, and mediators' preferences shaped how information moved into and within North America" (7). Taylor identifies trends in the data and places them in political context. For example, he illustrates how the appearance of new foreign newspapers in the early republic meant newly independent Americans were no longer limited to British trade or British newspapers. Taylor relies heavily on this database, both to frame his questions and to reach conclusions, but readers see little of his analysis directly. Tables or charts, either in the text or in appendices, might have helped. In his 2019 article in the JER, for instance, Taylor includes several charts [End Page 491] to help his readers visualize the trends he is describing.1 Taylor, as a digital historian, might also have been able to present this data analysis in ways not possible in a traditional monograph. Taylor frames his analysis using clever turns of phrase. For instance, Taylor uses the term mediation revolution, rather than media revolution, to underscore how it was the process of communications, more so than the technology, that changed in the eighteenth century. Transatlantic communications became "more formal, centralized, and hierarchical," even as they became more popular, due to the establishment of postal networks and newspapers (21). Taylor's point—that the growth of print-based communications in the eighteenth century did not automatically equate to democratizing of communications—is important and well-made. Yet while the term mediation revolution is novel, the concept of mediation in communications studies is not new, even among studies of print culture in the revolutionary and early republic periods. Taylor makes a narrower but more original intervention when he argues that the increase of mediation in transatlantic communications fed colonial fears of being misrepresented to the metropole. He adds, "The belief that misrepresentation stood at the core of the crisis of the British empire, and the conviction that it could be fixed, allowed the crisis to stretch through a decade of futile protest" (63). Taylor adds to existing scholarship on the partisan newspaper culture of the early republic, by historians like John L. Brooke, Trish Loughran, Jeffrey L. Pasley, and David Waldstreicher, by taking a continental view with comparisons to Spanish Louisiana and British Canada.2 By contrasting the coverage of the French Revolution in British–Canadian newspapers with their American counterparts during the same month, Taylor shows how different the news streams had become after American independence. The wide variety of foreign news sources also allowed [End Page 492] printers to choose the news that they preferred and reinforced the preexisting partisan viewpoints of their readers. For instance, Republican printers preferred sources direct from France whereas Federalist printers relied more on the British papers for news of the French Revolution. Taylor argues that partisan printers constructed such contrasting perspectives that from their separate sources that, by the end of the 1790s, there were "separate Republican and Federalist systems of knowledge" (164). In another play on words, Taylor explains that American readers saw the French Revolution as...
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".