Bibliographic record
Abstract
Les intrts amricains, autant de la marine marchande que d'autres entreprises engages dans le commerce extrieur, ont exig de fortes rponses gouvernementales au mal-traitement par d'autres puissances des vaisseaux battant pavillon des tats-Unis dans la dernire partie du 19me sicle. L'article actuel argue du fait que ces demandes ont russi. Dans certains cas le gouvernement des tats-Unis a entrepris des reprsailles de force, et dans les annes 1880 le gouvernement a commenc renforcer sa marine de guerre. Les dirigeants amricains ont t influencs par une crainte parmi l'lectorat qui le dclin abrupte, depuis la fin de la guerre civile, de la marine marchande, jadis de grande importance, et de la marine de guerre des tats-Unis aurait eu comme consquence que les tats-Unis puissent tre considrs avec mpris par d'autres nations. De ces craintes a merg un culte du drapeau. Cette insistance que le drapeau soit respect et dfendu l o il naviguait a aliment un nationalisme et un expansionnisme amricains qui ont men vers la dclaration de la guerre avec l'Espagne en 1898. Le culte du drapeau a galement contribu l'entre amricaine dans la premire guerre mondiale, comme rponse directe aux attaques des sous-marins allemands sur les navires marchands battant pavillon amricain.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 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".