Sir Frederic Shedden: The Forerunner
Bibliographic record
Abstract
Sir Frederick Shedden occupies an interesting and perhaps unique place in any consideration of the great mandarins of the Commonwealth Public Service who flourished, exercised their power, and helped to build modern Australia in the quarter of a century after the end of the Second World War. In many respects he fitted neatly into this characterisation – he was the secretary of the Department of Defence from 1937 until 1956; he wielded great power in the Defence group of departments; he was a key adviser to the prime minister; and he helped\nshape many of the instruments of government. But in other respects he was different. Unlike his contemporaries from this period, he had been secretary of his department since 1937, that is from before the Second World War. Although he had almost completed a university degree in commerce, he was not especially concerned with economic issues. By the mid-1950s, his power and influence\nwere waning, and he stepped down as departmental secretary almost two years before he formally retired. Further, unlike other mandarins, he refused to move\npermanently to Canberra, and worked in Melbourne for his entire career.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.103 | 0.039 |
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".