A Selection of Gifts to Special Collections from Queen's Alumni
Bibliographic record
Abstract
A Selection of Gifts to Special Collections from Queen's Alumni \nLibary Exhibit, September - October 2001 \nPresented for Homecoming Weekend, September 2001, this exhibition is one way of saying, \n“Thank you” to all our donors. It represents only a sampling of the many generous gifts to Queen’s \nLibraries received from alumni past and present. We acknowledge them with gratitude. Gifts-inkind \nand benefactions are vital to the ongoing development and enrichment of our research \nresources. \nThe Donors honoured on this occasion are: \nJohn Buchan (LLD ’36), \nPrivate Library purchased for Queen’s by Col. R.S. McLaughlin (LLD ’46) & Mrs. Adelaide \nMcLaughlin (LLD ’51); \nHelen K. Garrett Memorial Fund, \nEstablished by Dr. Thomas Garrett (Meds ’71). Helen Garrett (1946 -1970) was a former \nemployee of Queen’s University Libraries; \nThomas Dow Macgillivray (Arts ’02, Meds ’05), \nCollection donated by George B. Macgillivray (Arts ’37); \nRoland Michener (LLD ’58) \nGovernor General of Canada (1967-1974); \nLorne Pierce (Arts ’12, LLD ’26) \nPrivate Library and Edith & Lorne Pierce Endowment; \nDr. Ronald Burns Ross (Arts ’43, MA ’45); \nDr. Marian Webb (BA ’69) Botanical Collection; \nJeannie & Vero Wynne-Edwards Collection, \nDonated by Dr. Janet Sorbie (MSc ‘69) & Hugh Wynne-Edwards (MA ’57, PhD ’59) & families.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.460 | 0.315 |
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".