President's Award: Barbara Young
Bibliographic record
Abstract
The following are comments made by Dr Barbara Young upon the occasion of her being recognized as The 2016 Presidents Award recipient for the RV Tucker Study Clubs.Welcome to the homeland of our beginnings – the Pacific Northwest. Seattle has always been a very special meeting place for our Academy.I'd like to thank Carol Klingensmith for selecting to recognize me tonight. There are so many wonderful members that should be standing up here that I know the task was difficult. Carol comes from a line of amazing President's of this Academy that I have served with during my term as Editor. She will always be special in my heart. During her term as President, we lost our great Mentor, Dr. Tucker. Carol has served the Academy with grace and compassion during such a difficult time. She honors us all.It's quite an honor to be a recipient of the President's Award.There's no feeling like it. Do you melt or do you glow? I guess a little of both because it is humbling.I'd also like to thank the Executive Council for allowing me to serve as Editor for the Lineangle Newsletter. Thank you Margaret Webb for nominating me. Thank you Jim Deckman, who preceded me as Past Editor – for scratching out on a napkin everything I needed to know, during a clinical critique session in Vancouver. Thank you Dave Thorburn for guiding me. Thank you Warren Johnson for honing my understanding of what it takes to “make it shine.”I was never at a loss for the next story. The many articles each of you submitted filled the pages. Bringing such a diverse Academy together became great fun for me. Whenever I came to a fork in the road and had to make a decision on how to make the issue different and more interesting, I had to decide whether I should I go to the right or to the left. Each turn was something new and unknown. But, what I didn't know was that the roads converged as one again, as with many things represented by this Academy.I'll let you in on a secret I learned from Dr. Tucker, Warren Johnson, Rich Stevenson, Ted Kanamori, and my wonderful husband, Dr. Stan Siegel; They have taught me how to better “Honor my Life.” I in turn, make it a point to honor someone everyday. Your trademark is your honor.Tonight I'd like to honor my Family and my Peers ---Past Presidents of this Academy during my term as Editor:Randy Allen, Barry Evans, Bruce Small, Andreas Bien, Maureen Andrea, Manuel Cordero, Dana Otterholt, and Carol Klingensmith.There's one more very, very special person I need up here:Ron Gusa - The Academy's creator and first Editor of the Lineangle Newsletter. Thank you Ron.As these people stand, I want you to know what DR. TUCKER said to me once, in his easy going way:“There's nothing like it….. It's a profession where… it's amazing how people from all over the world become such good friends.”“There's really nothing like it anywhere.”I would like each of you to know how amazing you are.And when I look at this plaque, know that I share this honor with you.Bravo!!!
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.153 | 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".