Bibliographic record
Abstract
Abstract Chapter 9 and the corresponding Ch. 14 in Part Three of the book offer brief sketches of the institutionalization of the military and fiscal powers granted by the US Constitution, and of the uses made of them by the Federalists in the 1790s. Gives a historical account of the uses made by the national government during that period of the military powers that it was granted by the Constitution. Aims to make a judgment on the political achievement of the Federalists that hinges on the extent to which they managed to translate their principles into action when they transformed the articles of the Constitution into the policies and institutions of the new national government. Part of the discussion also addresses the fact that during the quarter century following the First US Congress, the USA had to respond repeatedly to events originating in Europe far beyond the federal government's control, and overall, drew advantage from the warfare that engulfed Britain, France, and Spain. It is noted that is not easy to answer the question of whether the federal government had any part in making this possible, but a cautious answer based on works of diplomatic history is that the reform of the federal government did make a difference to the actions of European governments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".