Bordering a War: Transnational Volunteers to the American Civil War from the Eastern Townships
Bibliographic record
Abstract
Abstract: Transnational volunteering during the Civil War by soldiers born in British North America (BNA) continues to intrigue Canadians. Nonetheless, distinguishing between those who crossed the border to enlist and the many BNA-born soldiers already living in the United States has proven difficult. With a new database of volunteers who left the Eastern Townships to enlist in Vermont, this article assesses three propositions drawn from historians' work. It refutes the idea that transnational volunteers were primarily mercenary, enlisting late when bounties were high. It partially confirms the proposition that enlistment was an immigration strategy. The third proposition that transnational volunteering was a borderland practice of those with close ties of family or religious practice to the United States holds for these border crossers. Abstract: L'enrôlement des volontaires transnationaux en provenance de l'Amérique du Nord britannique (ANB) pendant la guerre de Sécession américaine suscite toujours l'intérêt des Canadiens. Néanmoins, il s'avère difficile de faire la distinction entre ceux qui ont traversé la frontière pour s'engager et les nombreux soldats nés en ANB qui vivaient déjà aux États-Unis. À partir d'une nouvelle base de données sur les volontaires qui ont quitté les Cantons-de-l'Est pour s'enrôler au Vermont, cet article évalue trois propositions tirées de travaux antérieurs réalisés par des historiens. Il réfute l'idée que les engagés volontaires transnationaux étaient principalement des mercenaires, arrivant tardivement lorsque les primes étaient élevées. L'analyse confirme en partie la proposition selon laquelle l'engagement était une stratégie d'émigration. La troisième proposition, à savoir que le volontariat transnational était une pratique frontalière de ceux qui avaient des liens familiaux ou religieux étroits avec les États-Unis, est valable pour ces volontaires transnationaux.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".