Honorary Life Membership Award: Emeritus <scp>P</scp>rofessor <scp>P</scp>eter <scp>H</scp>olland (<scp>U</scp>niversity of <scp>O</scp>tago)
Bibliographic record
Abstract
Citation In 2008, the NZGS presented Peter with its most prestigious award, that of Distinguished New Zealand Geographer. Over a long and distinguished career, Peter has published five books and some 64 journal articles and book chapters, and since 1983 he has supervised 58 masters and PhD theses. His primary research focus has been on the biogeography, ecology and environmental history of New Zealand, and in this regard he has made a sustained and significant contribution to New Zealand scholarship for several decades. He has also researched and published on these themes in Kenya, Canada and South Africa. Peter's services to the broader academic environment in New Zealand include membership of NZQA panels, serving on and leading numerous academic audits, and broad participation in an advisory capacity in a range of academic activities. In addition, he has been an active member and supporter of numerous community-based activities. Peter Holland received the title of Honorary Life Member (Fellow) in recognition of his very considerable contributions to the NZGS and to Geography in New Zealand.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.226 | 0.130 |
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".