Ma première carte : intéresser les nouveaux étudiants à la communication cartographique
Bibliographic record
Abstract
Ce texte relate un exercice d’expression cartographique effectué lors du premier cours de design cartographique offert aux étudiants de première année universitaire. À main levée, sans autres moyens que les crayons disponibles dans leur sac, ils avaient à dessiner une carte devant mener chez eux un visiteur étranger arrivant au principal aéroport (Bagotville) de la région du Sague-nay—Lac-Saint Jean au Québec (Canada). L’expérience démontre qu’une bonne connaissance de l’espace régional et de quelques rudiments de communication graphique sont les conditions es-sentielles pour que les chances de succès se concrétisent. Les exemples proposés indiquent que les réalisations des étudiants prennent des formes très variées surtout en termes de lisibilité, de clarté, d’informations, d’orientation, d’échelle et d’efficacité. \n \nThe following text concerns an exercise in cartographic expression carried out during the first course in cartographic design offered to first-year university students. With no other means than the pencils available in their bag, each student had to draw a map to direct to his/her home a foreign visitor arriving at the main airport (Bagotville) in the Saguenay—Lac-Saint Jean region (Quebec, Canada). The experience shows that a good knowledge of the region and some rudiments of graphic communication are the essential conditions for success. The examples given indicate that the students’ achievements take very varied forms, especially in terms of readability, clarity, information provided, orientation, scale and effectiveness.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.008 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.004 |
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".