Walking with Janet Cardiff, Sitting with Massimo Guerrera, and Eating Apples with R. Murray Schafer
Bibliographic record
Abstract
As Anthony Robbins once said “If you do what you have always done, you will get what you have always got.” Now more than ever museums and galleries are seeking to attract new audiences and find innovative and meaningful ways to engage visitors. While these institutions aim to respond to their responsibility to provide access to their collections, new modes of interpretation are needed to ensure they reach a wider audience. This audience must include the ever-growing population of visitors with disabilities, who for too long have been denied their human right to cultural heritage. When it comes to visitors who are blind or partially sighted, many art galleries are left scrambling to find ways to provide quality programming and access to their all too often “untouchable” art collections. Unfortunately, sometimes this means that visitors with visual impairments are segregated for specialized programming, isolating them from their sighted friends and family members. This article will provide examples of how The National Gallery of Canada has adapted public programs and developed new ways for diverse audiences of various ages and abilities to come together in inclusive settings. Furthermore it will explore how interactive and participatory art can be instrumental in providing meaningful museum experiences and opportunities for multisensory engagement, which in turn offer an entry point for new visitors. Visitors do not require a PhD in art history to “get it,” they need simply to show up and participate. What is notable here is that these experiences are not watered down or simplified—in fact the contrary. The outcomes of these programs and exhibitions suggest that
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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.140 | 0.064 |
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".