E. Salmon, the Story of the Empire (London: George Newnes, 1902), pp. 154–163.
Bibliographic record
Abstract
Edward Salmon was the editor of United Empire , the journal of the Royal Colonial Institute. In The Story of the Empire , Salmon saw the Empire as a success story, having withstood downturns such as the loss of the American colonies, and discontent in Canada in Australia and at the Cape at the beginning of Queen Victoria’s reign. Had she been in full command of the facts, Salmon argued, Queen Victoria would have concluded that the Empire was ‘doomed to dissolution’. Cobden and Bright of the Manchester School had argued that colonies were too costly to acquire and yielded few trade benefits. This pessimism had also been circulated in the work of Adam Smith and John Stuart Mill. Conditions in New South Wales were chaotic, as settlers were pitched against convicts, and in New Zealand 10 per cent of the white settlers were escaped convicts. Empire had then gradually been reconstituted during the rest of Victoria’s reign. The chapter included here is the penultimate chapter, titled ‘Progress All Round’ .
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.038 | 0.015 |
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".