Art is Not Research. Research is not Art.
Bibliographic record
Abstract
Art is not Research. Research is not Art. is a multimedia, multi-site participatory installation by a collective of artists and researchers from Calgary, Toronto, and Lancaster; it is informed by these contexts. It reflects the tensions between how “participants” are treated in participatory art and interaction research. It offers a framework through which we can explore how epistemologies might evolve in a blending between Art and Research. Visitors download the paper to read, critically reflect on the relationship between art and research, and experientially engage with the material through a series of creative prompts. A performance variation of the piece will be performed in-person and online through the ACM SIGCHI Conference on Human Factors in Computing Systems alt.chi track.
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 | 0.078 | 0.142 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.013 | 0.112 |
| Scholarly communication | 0.041 | 0.042 |
| Open science | 0.005 | 0.014 |
| Research integrity | 0.014 | 0.026 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".