Christine G. Kruger & Sonja Levsen (ed.), War volunteering in Modern times from the French Revolution to the Second World War
Bibliographic record
Abstract
Cet ouvrage est le fruit d'un séminaire tenu à l'université de Tubingen en 2007, et des échanges auxquels il donna lieu ultérieurement, dans le cadre du Centre de recherche de cette université dénommé Les expériences de guerre, la guerre et la société à l'époque moderne.Dans l'introduction de ce volume de près de trois cents pages, qui rassemble quatorze communications, les auteures explicitent ses principales lignes de force.Elles estiment que cet ouvrage comble une sorte de carence historiographique envers le phénomène du volontariat en période de guerre tandis que l'attention des chercheurs et chercheuses s'est bien davantage portée sur la conscription, la désertion, voire l'objection de conscience.Or ce phénomène a pourtant donné naissance aux XIXe et XXe siècles à un mythe fondateur, essentiel pour la construction des nations et le roman national que certaines élaborèrent.En effet, le combattant volontaire devient l'incarnation par excellence de l'identification entre l'individu et la nation.Ce relatif désintérêt des historiens, sauf à propos des volontaires de la Révolution française et de leurs homologues britanniques de la première guerre mondiale, laisse donc dans Christine G. Kruger & Sonja Levsen (ed.), War volunteering in Modern times fr...
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.005 |
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".