Canadian Math Kangaroo Contest Workshop Organizers:
Bibliographic record
Abstract
The First Canadian Math Kangaroo Workshop was planned for a long time. The event, generously supported by BIRS and PIMS, became a reality in November 2010. Math Kangaroo city coordinators from the Greater Toronto Area, Ottawa, Montreal, St. John’s, Winnipeg, Calgary, and Edmonton as well as volunteers from Edmonton and Calgary attended the workshop. Also, there was one participant from a city intending to organize the contest in the future. Eleven presenters gave talks, two of them undergraduate students. 1 Overview of the Field In 2010, the international Math Kangaroo contest involved over 5.5 million students and hundreds of mathematicians from 46 countries internationally. The 2010 Canadian edition of the competition was administered in Ottawa, the Greater Toronto Area, Edmonton, Calgary, Montreal, St. John’s, Winnipeg, Sudbury, Langley, and Lunenburg. Almost 1200 students participated in the contest, and hundreds were involved in various training and learning activities prior to the contest day. The Math Kangaroo outreach programs focus on providing students in the age range of 8 to 18 with the opportunity to experience and explore mathematics. The organization’s purpose is to share the joy of mathematics with youth through an annual math competition and short-term and year-long training opportunities. Since joining the International Association in 2006, the Canadian Math Kangaroo is continuously seeking ways to further expand its geographic reach and its high-demand unique programs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.013 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.128 | 0.037 |
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".