Bibliographic record
Abstract
The War of 1812 may have been a small and inconclusive war, but it had a profound and lasting impact of all the belligerents. The war may be largely forgotten, but it left a huge legacy that is still evident today. Wars can best be measured by their consequences, and the legacy of this war was both multifaceted and lasting. The conflict shaped both the United States and Canada as well as their relationship with Great Britain for nearly a century thereafter. It helps to explain how the Anglo-American alliance originated and why the British welcomed the Pax Americana in the twentieth century, as well as why Canada never joined the American Union and why American expansion after 1815 aimed south and west rather than north. It was during the War of 1812 that the great Shawnee leader Tecumseh earned his reputation, Laura Secord became famous, and Andrew Jackson began his rise to the presidency. Its impact on American culture was also far reaching and produced ‘The Star-Spangled Banner’, Uncle Sam and ‘Old Ironsides’, amongst other symbols of United States nationhood.
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.016 | 0.028 |
| Scholarly communication | 0.016 | 0.008 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".