L’enseignement de la blockchain pour les étudiants en comptabilité : état des lieux et leçons issues du Top 50 mondial des universités.
Bibliographic record
Abstract
La Blockchain est présentée comme une technologie disruptive en comptabilité, mais les applications concrètes tardent à se développer et à se généraliser. Une raison probable est le niveau de formation des professionnels à cette innovation, ce qui conduit à questionner comment s’enseigne la blockchain dans les universités. Cette recherche étudie les curricula des universités du Top 50 mondial (classement de Shanghai). Il apparaît cinq axes de cours : 1) approche métier ; 2) approche double ou triple compétence ; 3) approche entrepreneuriat et développement des affaires ; 4) approche sectorielle ; 5) approche critique et holistique. Nous discutons ces résultats au prisme des théories sociales, et proposons des curricula -types pour chacun de ces axes de cours.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".