Exploring Institutionalised Esport in High School: A Mixed Methods Study on Wellbring
Bibliographic record
Abstract
These proceedings represent the work of contributors to the 12th European Conference on Game Based Learning (ECGBL 2018), hosted this year by SKEMA Business School, Sophia Antipolis, France on 4-5 October 2018. The Conference Chair is Dr Melanie Cuissi and the Programme Co-Chairs are Dr Sophie Gay Anger and Dr Margarida Romero. ECGBL is a well-established event on the academic research conference calendar and now in its 12th year the key aim remains the opportunity for participants to share ideas and meet the people who hold them. The scope of papers will ensure an interesting two days. The subjects covered illustrate the wide range of topics that fall into this important and ever-growing area of research. For the 5th year the conference has also played host to the International Educational Games Competitions. The opening keynote presentation is given by Dr Sylvester Arnab from Coventry University's Disruptive Media Learning Lab (DMLL) on the topic of “The Magic Circle of Playful and Gameful Co-Creation”. Then an afternoon keynote will be given by Dr Eric Sanchez from the University of Fribourg, Switzerland, with the talk entitled “Don’t Forget the Beans!”. The second day of the conference will open with an address by Dr Jacob Habgood from Sheffield University, who will be discussing “Do Books Work? (and other questions we probably shouldn’t ask)”. With an initial submission of 205 abstracts, after the double blind, peer review process there are 90 Academic research papers, 7 PhD research papers, 3 Masters Research papers and 15 work-in-progress papers published in these Conference Proceedings. These papers represent research from Australia, Austria, Bahrain, Bulgaria, Canada, China, Cyprus, the Czech Republic,Denmark, Estonia, Finland, France, Germany, Greece, Guatemala, Hong Kong, India, Indonesia, Iran, Ireland, Israel, Italy, Jamaica, Japan, Malaysia, the Netherlands, Norway, Poland, Portugal, Qatar Romania, Russia, Slovakia, South Africa, Spain, Sweden, Switzerland, Thailand, the UK, and the USA.
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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 | 0.024 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".