Okanagan Waterways Past, Present and Future: Approaching Sustainability through Immersive Museum Exhibition
Bibliographic record
Abstract
This paper presents Waterways Past, Present and Future, a research project and exhibition in Okanagan Syilx territory, aimed at increasing awareness of the relationship between people and water towards catalyzing sustainable water practices. The exhibition’s multi-channel audio-visual media was designed to immerse, provoke, destabilize, transform and move visitors to take responsibility for water. Drawing on many ways of knowing and doing in the creative process, the exhibition opens different entry points to the research, thus encouraging an interdisciplinary and cross-cultural audience to engage with it. Waterways’ contribution to sustainability discourse lies in its empowerment of collaborative inquiry as a way of knowing, understanding and representing our world. The epistemological dimensions of the exhibit present multiplicities embedded in the social life of water, inviting dialogues, shaping cultural narratives and developing new forms of creativity. Through the sensual process of immersion and activation of lateral thinking, the exhibition facilitates connections across cultures, connections that act as agents for social transformation. Waterways’ experiential journey transcends our personal and dominant socio-cultural patterns, reaching beyond normative structures to new creative realms shared ethical space.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.000 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".