Online MBA Student Visits Campus for Graduation
Bibliographic record
Abstract
Robyn McBrady graduated from the University of North Dakota on Saturday, May 14. It was the first time she’d ever stepped foot on campus. A native of Kensington, Minn. McBrady was one of more than 2,100 UND students who were eligible to receive degrees from the institution at the General Commencement exercise at the Alerus Center. McBrady attained her Master’s Degree in Business Administration exclusively online and with other distance-learning means through UND’s Office of Extended Learning. McBrady explains that she has been to Grand Forks but she had never made it to the UND campus before Saturday, despite earning enough credits for a UND master’s degree. Kensington is a small Minnesota community of about 300 people, southeast of Alexandria, Minn., in Douglas County. It’s about 180 miles southeast of Grand Forks, as the crow flies. UND’s online MBA program is administered through the College of Business and Public Administration and the Office of Extended Learning. Of the 2,100 students who were eligible to graduate, more than 1,200 of them took part in Saturday’s ceremony. Unlike many of her fellow graduating classmates who spent at least four years working toward their degrees on campus here at UND, McBrady was quite literally – here and gone. She was scheduled to arrive in Grand Forks from her home in Kensington sometime late morning Saturday before the commencement ceremony at 1:30 p.m. With degree in hand and after a quick interview with a local Grand Forks TV station, she was on her way home again.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.641 | 0.564 |
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".