EDUCAUSE 2019 French Delegation Report - EN: Visits to University of Chicago, Northwestern University & Concordia University
Bibliographic record
Abstract
For the seventh consecutive year, a French delegation was formed to participate to the EDUCAUSE AnnualConference. Since 2013, this initiative has been structured around complementary profiles from the digital worldof the French Higher Education, all of them being keen to open up to the international arena in order to findsources of inspiration and points of comparison, but also to highlight remarkable achievements. From an initialphilosophy of simple attendance, which prevailed during the first years of this delegation, we have graduallymoved to a resolutely more active approach, at various levels.The members of the Delegation steering committee actively participate to the life of EDUCAUSE :• The delegation communicated from 2012 to 2019 in the framework of the Annual Conference (six sessionsand five posters) and the ELI conference1 (three sessions).• Three members are part of the proposal reviewers since 2015 to evaluate papers submitted to the AnnualConferences and ELI.• One member was selected on behalf of CSIESR on the 2019 program committee.• Since 2018, two members have been part of the panel of experts selected for the drafting of theEDUCAUSE Horizon Report2.• Two members participate to EDUCAUSE working groups, the Learning Space Community Group, theBlended and Online Learning Community Group and the Extended Reality XR Community Group.• Two members under CSIESR and EUNIS work in the CHEITA group which is an informal federation of sisterEDUCAUSE associations around the world (Europe, Australia, France, Japan, New Zealand, UnitedKingdom, Netherlands).• Two members under CSIESR and EUNIS worked for the EDUCAUSE International Task Force which met inwebconference from January to October 2019 to produce a recommendations document on EDUCAUSE'sinternational actions.The recognition of these different levels of involvement has enabled us to forge privileged links with EDUCAUSE,and in particular its executive members (President, Vice-Presidents and Directors), and more generally within theNorth American University community, with whom some formal collaborations have already been establishedover the years. These links contribute to the achievement of our fundamental objectives: to exchange, raiseawareness, inform and share in order to support the development of digital technology in French HigherEducation.Our traditional restitution is a concrete expression of this desire, and has become a major annual event that weknow being appreciated. The accompanying report, for its part, is becoming increasingly widely distributed, andis based in particular on the present English translation which we quickly took note of. Outside Europe, it isexpected and read every year in the United States, Canada, Japan, Singapore, Australia and New Zealand. Thisnew edition of our report follows on from the restitution held in Paris on 12 February 2020 in the premises of theAMUE. It covers the usual three university visits (University of Chicago, Northwestern University in Chicago, andConcordia University in Montreal), and the various workshops attended at the EDUCAUSE Conference itself. Itcan also be supplemented by the various tweets posted by the delegation under the hashtag #EDU19fr.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.154 | 0.049 |
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".