La Royce Batchelor: A Black Belt in Business and Karate
Bibliographic record
Abstract
Karate is about teaching people self-defense. But for University of North Dakota College of Business faculty member and second-degree black belt La Royce Batchelor, it's also about good mental health. "While I was teaching at Red River College in Winnipeg, one of my students was deeply, deeply involved in Karate," Batchelor said. "Our family was going through a really stressful time and he recommended Karate for my oldest son, Thomas. I had to take him anyway, and I got interested. Next thing I knew, I was in Karate. "I started Karate for the physical and mental well-being. It is high energy and builds confidence and a sense of peace. But now it's because I love to see that in others; when they get excited about it and when they start coming to every class." Batchelor, currently a faculty member in the UND's Entrepreneurship program, part of the College of Business and Public Administration, got involved in Karate at age 35. When she arrived at UND she wanted to continue training. That's when she and her son, who is a first-degree black belt, started the Hisshou Karate Dojo. "Yes, it's a Karate dojo, but we are more than that," Batchelor said. "We have a lady who teaches Tai-Chi and someone who teaches Reiki." The dojo, located in the Grand Cities Mall in Grand Forks, is partnered with the UND Karate Club. The club, which already has brought home eight medals from an international tournament, will compete this weekend (Oct. 5-7) at the 2012 International Shotokan Karate National Karate Tournament in Arizona. Hissou Karate Dojo's 90-minute classes are held Monday through Thursday at 7 p.m. and Saturdays at noon. There are 17 students enrolled. Karate classes are open to people of all ages. "We're not so much a club as we are a family," Batchelor said. "We embrace newcomers the same way we embrace those who have been with us for years. That's one of our strengths." Batchelor received her first black belt in May 2009 and has just completed her second-degree black belt. There are 10 belt levels called 'Kyu' that lead you to black belt, and then there are 10 degrees of black belt called 'Dan'. "I'm just beginning my black belt journey," Batchelor said. "Anything below the black belt, you're still learning what Karate is. Anything above the black belt, you're learning what Karate is to you."
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.005 |
| Scholarly communication | 0.008 | 0.008 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.004 | 0.012 |
| Insufficient payload (model declined to judge) | 0.120 | 0.025 |
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".