A Multidisciplinary Place-Specific Art Course Outline for the CEGEP Level
Bibliographic record
Abstract
This thesis takes a close look at art practices investigating the physical, experiential and social dimension of place, and at how these art forms could be better integrated in the CEGEP Visual Arts program in Quebec. It consists of a research-creation project involving a heuristic study, which resulted in the design of a place-specific course outline for this teaching-level. The following research question guided my investigation “how can an enhanced understanding and explication of my endeavor in creating a place-specific body of work contribute to the design of a place-oriented art course outline for young adult learners?” I first assessed different kinds of artistic approaches by conceiving four projects inspired by my explorations of Park Jarry in Montreal, which culminated in a more ambitious body of work. The analysis of the documentation gathered during this process established a correlation between the art-making session, an enhanced connection to the place, as well as an improved pedagogical understanding of this art form. This manifested itself in the adaptation of the artworks into four assignments. The first project aims for students to become more familiar with the given area through an exploration, documentation and research exercise. It is followed by an activity based on the movement of process art. The third activity proposes to explore the techniques of pinhole cameras and cyanotype. Finally, the final project encourages students to investigate more in depth an element of the place. The thesis text includes photographic documentation of the artworks and a full-fleshed syllabus.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.042 | 0.007 |
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".