Annual UND Hagerty Lecture Series feature two journalists at separate events in Grand Forks and Bismarck
Bibliographic record
Abstract
Lectureship series was established through an endowment to benefit the Communication Program This year, for the first time, the University of North Dakota will present two lectures – in Grand Forks and another in Bismarck -- as part of its annual Hagerty Lecture Series. The Grand Forks lecture, on March 24, will feature David Bjerklie, a UND graduate who writes about science for children. He will focus on responding to the profound questions about science that children ask at 7 p.m. Tuesday, March 24, in the Community Room of the Grand Forks Herald, 305 Second Avenue North in downtown Grand Forks. Enter through the alley door. The Bismarck event will feature Alexander Panetta, Washington, D.C., correspondent for the Canadian Press. He'll discuss Canadian approaches to issues arising along the international border at 4:30 p.m., Tuesday, April 21, at the North Dakota Heritage Center on the capitol grounds. David Bjerklie: Bjerklie grew up in Minot, N.D., and studied biology and anthropology at UND. As a lab and field assistant, he studied spotted sandpipers on a small island in a large lake in Minnesota. He has written on a wide range of science, medicine, technology and environment topics for Time Inc., since 1984, serving as a science reporter at Time magazine, a writer at Time books and editor at Time for Kids. He is the author of children's books on butterflies, agriculture and environmental justice. In 1989-90, he spent a year as a Knight Science Journalism Fellow at the Massachusetts Institute of Technology. In 2014, he attended the 65th annual Lindau Nobel Laureate meeting in Germany and spent three weeks in Antarctica as a National Science Foundation Media fellow. Some of his recent stories for Time for Kids have been on wind sculpture, the global explosion of jellyfish and the mathematics of juggling. He has also written chapters in recent Time books on the search for life in the universe, the use of DNA in the courtroom, artificial intelligence, the nature of collaborative genius and current research in child psychology. Alexander Panetta: A Montreal native, Panetta has worked for Canada' national news agency -- the equivalent of the Associated Press in the United States -- for 16 years. He's covered federal and provincial politics for most of that time. He's also covered international news, including the war in Afghanistan and the disastrous earthquake in Haiti. Since the fall of 2013, he's been in Washington, D.C., where he reports on U.S. stories for a Canadian audience, with a special emphasis on politics and cross boundary issues. Hagerty Lecture Series: The lecture series is named for Jack Hagerty, longtime editor of the Grand Forks Herald. When Hagerty retired in 1984, The Herald established the lectureship through an endowment to the University's Communication Program. Hagerty was the husband of Marilyn Hagerty, the Herald's food writer, whose reviews have been an Internet sensation.
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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 | 0.002 |
| 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 | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.433 | 0.273 |
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".