Bibliographic record
Abstract
Gordon Dodds leaves Canadian archivists a rich legacy.He was one of the giants who animated our professional infrastructure and its intellectual underpinnings.As first president of the Association of Canadian Archivists, editor of Archivaria, educator, author, and administrator, his many accomplishments are important milestones.Perhaps greater yet was his ability to inspire in others what being a professional archivist meant in the later twentieth century.As Gordon now joins history, we may well reflect on how he shaped our own history.William Gordon Dodds was born on 28 April 1941 in Newcastle-upon-Tyne, in Northern England.He spent twenty years in the village of Wideopen, and summers along the wild Northumbrian coasts.His surroundings were replete with traces of the Roman Empire, early Christianity, and the first landmarks of the Industrial Revolution.From these he absorbed the love of history that formed the core of his undergraduate and Master's studies at Durham University, with research theses ranging from supplying corn to the Roman army in Britain to the Northumberland's turnpike trusts.History also animated his first book, co-authored with Lyall Wilkes, Tyneside Classical: The Newcastle of Grainger, Dobson and Clayton (1964).Gordon worked one undergraduate summer at the Northumberland County Archives.There he admired the enthusiasm of the county archi-ARCHIvARIA 71 (Spring 2011)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 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; 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".