Bibliographic record
Abstract
With the publication of in the Streets: Merchant Seamen in the Politics of Revolutionary America in 1968, Jesse Lemisch helped to transform the ways in which historians viewed the American Revolution. With ordinary seafarers, not founding fathers, at the centre of his analysis, Lemisch argued forcefully that the popular politics of the waterfront in particular, seafarers' opposition to the British navy's repeated and barbaric use of the press to man its undermanned ships braced the unfolding imperial crisis over taxa tion and representation with more radical language, behaviour, and objectives. Working from a PhD thesis completed at Yale University in 1963, Lemisch sought to rescue jolly Jack Tar with his bowed legs, baggy trousers, and foul mouth from the romanticism of popular culture and mystifications of conservative historiography, and reveal him for he what was: a thinking, craving, assertive historical actor in one of the 18th century's most important political dramas. Impressment meant the loss of freedom, both personal and economic, and, sometimes the loss of life itself. The seaman who defended himself against impressments felt that he was fighting to defend his 'liberty,' and he justified his resistance on the grounds of 'right', Lemisch wrote. It
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".