Memories of Terry Erwin
Bibliographic record
Abstract
We were fortunate to have known Terry not only as an excellent professional coleopterist and an enthusiastic colleague, but also as a good friend. Entomological meetings for us came with an evening supper or two with Terry and the kind of laid-back personal catch-up that happens only among friends with long-term interest in each other’s lives. Through our connections with the University of Alberta and George Ball we were also happy members of Terry’s basal academic family. While we will join the rest of a broader scientific community in missing his presence in development of ideas about beetles, biodiversity and evolution, the kinds of work that Terry promoted will continue. We will, of course, be interested in following how the understanding of carabids and nature develops further from Terry’s contributions. This will most certainly continue to grow, partly through the efforts of those that he has influenced. Every practicing research scientist has some role to play in the great chain of discovery, and much of this volume is meant to celebrate Terry’s contributions and showcase how they have influenced the work of others. Our own more enduring sense of loss will flow from the personal interactions with Terry that were generally part of our timelines. Despite the sadness associated with such loss, our memories of interactions with Terry underscore a sense of joy and gratefulness for having connected with him interpersonally in life. Given Terry’s affable and social nature, many others will have such memories. Thus, when Lyubomir Penev asked us to coordinate a selection of ‘memories’ for this memorial volume, we were happy to undertake the task and gather together a selection of memories of our friend, Terry Erwin. What follows is a series of recollections by people who knew and worked with him from a number of perspectives during a broad range of his academic career. We are most grateful to those who have been willing to share their reflections. These are presented here as a way of reaching beyond Terry’s considerable scientific influence to also preserve some sense of his influence on the lives of people, and the ways in which he encouraged and inspired them. We thank all the contributors for their efforts and Diane Hollingdale for work to bring the included photographs to the best possible publication standard. John R. Spence Edmonton, Alberta David H. Kavanaugh San Francisco, California David R. Maddison Corvallis, Oregon
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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".