An Exemplary Whig: Edward Kent and the Whig Disposition in American Politics and Law
Bibliographic record
Abstract
Seventy men have held the office of Maine governor since statehood in 1820. In An Exemplary Whig David M. Gold outlines in rich detail the life and work of Edward Kent, who served as governor in the years 1838–1839 and 1841–1842. Following the lead of Michael F. Holt in The Rise and Fall of the American Whig Party (1999), Gold asserts that the political decisions that had the greatest impact on nineteenth-century Americans happened at the state level. As such, state governors deserve biographical reconsideration from historians. Kent graduated from Harvard University in 1821 and counted his classmate Ralph Waldo Emerson as one of his oldest friends. Rather than pursuing a career in letters, however, he became a Bangor lawyer and drifted into Whig politics. Gold suggests Kent toed the party line on most issues and was indeed an exemplary Whig: he supported Henry Clay's economics of national development and banking, opposed the expansion of slavery, and advocated temperance legislation (Kent was second only to Neal Dow, the father of the “Maine law,” in his long-standing support of stringent liquor laws). On other matters, though, he strayed from the flock. During the imbroglio with Great Britain over the Maine-Canadian border, Governor Kent sided with many Democrats in urging a far northern border and military preparations in case of invasion. His leadership on the northeastern boundary issue led Secretary of State Daniel Webster to tap Kent as one of the New England commissioners during negotiations with Lord Ashburton in the years 1841–1842. His opposition to slavery also had limits, Gold asserts. Rather than following radicals such as Senator Charles Sumner, the conservative Kent feared abolitionist agitation over the Fugitive Slave Law might topple the Union and Constitution. By the Civil War he had transitioned to the Maine Supreme Judicial Court, where, as a Republican justice for fourteen years (1859–1873), rather than turning to legal novelties, he applied the Burkean virtues of prudence and common sense to the law. “Kent's aversion to theorizing may have been related to his admiration for the common law,” Gold writes, When nineteenth century reformers sought to simplify and systematize the law, traditionalists, typically Whigs, defended the common law as the accumulated wisdom of the ages, safe from the momentary passions of political majorities yet flexible enough to adapt to fundamental social changes. (p. 207)
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.011 |
| 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".