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
Hearing Conflicts in Museums employs research-creation to reflect on site visits to the Canadian Museum for Human Rights, and to grapple with questions about listening in museums, as well as how to understand conflict and polyvocality. In this audio project you hear three researchers: Friederike Landau-Donnelly, Kirsty Robertson, and Sarah E.K. Smith. You also hear an auto generated voice that provides an institutional perspective, reading texts that draw from the museum’s website and policy documents, as well as scholarly articles. Through these multiple voices we aim to foreground our different perspectives, particularly, in light of our focus on multivocality. The project primarily draws on site recordings that reflect the acoustic space of the institution. These are from our research visits to the museum in October 2023 and additional recordings from 2024. We also include open source music from the Free Music Archive and clips from Free Sound. We hope the resulting piece provides one type of listening journey that can be accessible to off-site visitors.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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