Bibliographic record
Abstract
Canada in 1853, initially to work as a prospector, but later moving into business, farming and politics. He was elected to the Victorian Legislative Assembly in 1874 and later served as a delegate to the Australasian Federal Convention (1897–1898) and a senator representing the Free Trade Party (1901–1913). Malcolm’s father, John Neville Fraser (1890–1962), studied law at the University of Oxford, but on his return to Australia concerned himself largely with his work as a pastoralist. In 1926, he Married Una Woolf. Neville and Una had two children: Lorraine (1926–) and (John) Malcolm (1930–). The Fraser family lived at Balpool-Nyang near Moulamein in New South Wales before moving to ‘Nareen’, a station in western Victoria, in 1943. During this period Malcolm attended Tudor House School in New South Wales (1940–1943) and Melbourne Grammar (1944–1948). In 1949, he was admitted to the University of Oxford to study ‘Modern Greats ’ (Politics, Philosophy and Economics). After graduating, Malcolm Fraser returned to Victoria and decided to embark on a political career. He succeeded in being elected as Liberal member for the seat of Wannon in western Victoria at his second attempt in 1955. A backbencher under Menzies for ten years, Fraser gained his first cabinet post as Minister for the Army under Prime Minister Harold Holt in 1966. He went on to become Minister for
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 | 0.002 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.763 | 0.624 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".