Bibliographic record
Abstract
The British Empire of the later nineteenth century was an imposing sight. By 1900 it had grown to immense proportions, embracing nearly a quarter of the world’s land surface and almost one-third of its inhabitants. Not even Spain at the height of its glory had exercised control over so broad a swathe of the world’s peoples. It was, of course, an empire acquired and maintained largely by force. From Waterloo until the outbreak of the First World War there was scarcely a time when British troops or their British-officered colonial auxiliaries were not in action somewhere around the globe. On occasion, as in the Boer War, they found their resources stretched. Yet for the most part these were low-cost affairs involving what would now be called Third-World peoples, and as such very different from those long-drawn-out conflicts between Great Powers that bring about major changes in the international order. Compared to the centuries that preceded and followed it, the nineteenth century, so far as the British were concerned, was a period of relative equilibrium. For the most part they were more concerned with following Adam Smith’s advice and expanding commerce than acquiring vast territories, yet one thing led to another, and often it was easier simply to extend their rule than cope with troublesome neighbours or fend off rivals. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.171 | 0.067 |
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".