Bibliographic record
Abstract
The CFA Institute Research Challenge wrapped up its seventh competition on 12 April in London with a new global champion: Wroclaw University of Economics. The five-member winning team from Poland included Jan Kasperowicz, Katarzyna Kowalczyk, Piotr Lembas, Kamil Saklaski, and Marta Szudzichowska, who served as the team’s captain. Szudzichowska explained that in addition to extensive preparation for each challenge event, an important element of the team’s winning strategy was their ability to handle stress. To relieve pressure and regain their focus, the team enjoyed playing a card game called “Jungle Speed.” “In the end, before our final presentation, only one thing really mattered: how to deal with the stress,” said Szudzichowska. “The card game really helped us cool off and enabled us to go into the Q&A session with clear heads.” As part of the research challenge competition, students worked in teams to write an initiation-of-coverage report on their assigned subject company. Some teams are then invited to present and defend their “buy,” “sell,” or “hold” recommendation to a panel of industry experts. This is no small task. Students spend hundreds of hours preparing for the competition while enrolled in full course loads (sometimes at the graduate level), working, and managing other personal and professional commitments. Team member Kamil Saklaski learned many lessons from the experience, especially when it came to collaboration. “The research report that we had to prepare on KGHM Polska Miedź S.A. required different expertise, approaches, and ideas. Each of us improved our analytical skills while working on each section, keeping in mind the whole structure and the character of our investment story. On the other hand, we gained a lot of ‘soft skills’ too, like teamwork, time management, task planning, and a broad array of presentation skills.” More than 3,500 students from more than 775 universities participated in local competitions held in 55 countries this year. Winners from each local-level competition, organized by volunteers at CFA Institute member societies, advanced to one of three regionals hosted by CFA Institute: Asia Pacific (held in Kuala Lumpur on 23 February), the Americas (held in Toronto on 21 March), and EMEA (held in London on 11 April). The winners from each regional then advanced to the final competition on 12 April and included:
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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 | 0.008 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.014 | 0.015 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.052 | 0.012 |
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".