Bibliographic record
Abstract
Abstract This is the first in a series of biographies entitled ‘Children of the Golden Age’, the purpose of which is to describe the background and contributions of a number of significant living figures in polar research, all of whom began their scientific careers and earned their Antarctic spurs in the years following World War II. Bernard Stonehouse was born in Hull on 1 May 1926. Joining the Royal Navy in 1944, he trained as a pilot, and in 1946–50 served as meteorologist, second pilot, dog-sledger, and ultimately biologist with the Falkland Islands Dependencies Survey, mainly from Base E, Stonington Island, Antarctic Peninsula. His first biological investigation was a winter study of breeding emperor penguins. Returning to Britain in 1950 he read zoology and geology at University College, London. Doctoral research at the Edward Grey Institute of Field Ornithology and Merton College, Oxford, involved an 18-month field study of king penguins on South Georgia. Between 1960 and 1968, as senior lecturer, later reader, in zoology, at University of Canterbury, Christchurch, New Zealand, he continued Antarctic and sub-Antarctic research in McMurdo Sound and on the New Zealand southern islands. A Commonwealth Research Fellowship at the University of British Columbia, 1970–71, gave him opportunities for research in the Yukon. After developing undergraduate and postgraduate studies in environmental science at the University of Bradford, 1972–83, he joined the Scott Polar Research Institute as editor of Polar Record , thereafter forming the Institute's Polar Ecology and Management Group, and heading a long-term study on the ecological impacts of polar tourism. At SPRI he continues to combine the two factors that have always played an important part in his life: working in polar regions and communicating with the general public on issues of biology, the environment, and conservation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.016 | 0.005 |
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; both teacher heads 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".