Affective metadata for object experiences in the art museum
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Affective metadata for object experiences in the art museum explores the notion of affect as related to visitor experiences of artworks in a museum gallery setting, resulting in the specification of a data structure and knowledge organization system capable of methodically documenting these experiences. This proposed system presents an interdisciplinary view of museum object documentation that pushes the boundaries of what is conceptualized as object information worthy of documentation in order to adequately account for affective knowledge. Through an analysis of the literature – including affect and affect modeling, art museum information systems, and empirical aesthetics – and a visitor research study at the Art Gallery of Ontario, this thesis argues that affect needs to be considered as a salient dimension of art museum information infrastructures and metadata standards. One possible model for developing such a structure and corresponding standard is presented and validated using the results of this visitor research study.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 it