Bibliographic record
Abstract
When touring Australia in 1884, Lord Rosebery, who was later to become British Foreign Secretary, made a speech in Adelaide in which he referred to ‘the British Commonwealth of Nations’. 1 This is believed to be the first use in public of the term ‘Commonwealth’ in the context of a grouping of nations. It was not until 1926 that this concept was more precisely defined. Lord Balfour, a former Prime Minister, who had returned to office in 1922 as Foreign Secretary, described Britain and the Dominions as ‘autonomous communities within the British Empire, equal in status and in no way subordinate one to another in any aspect of their domestic or external affairs, though united by a common allegiance to the Crown and freely associated as members of the British Commonwealth of Nations’. 2 Five years later — in 1931 — this relationship was enshrined in the Statute of Westminster — an Act of the British Parliament which conferred on the Dominions of Canada, Australia, New Zealand, South Africa, Newfoundland and the Irish Free State the power to repeal or amend acts of the British Parliament which applied to them. It was this Act of Parliament which created what came to be known as Dominion Status. 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.008 | 0.022 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".