‘Whose Object is it Anyway?’ – Four Workshops at the Aga Khan Museum investigating the ‘Properties of Things’
Bibliographic record
Abstract
In October 2018, the Aga Khan Museum was invited to contribute to the conference ‘Properties of Things: Collective Knowledge and Objects of the Museum’, sponsored by Ryerson and Mount Allison Universities. The event was conceived to throw an innovative, and intellectually bold, multidisciplinary spotlight onto curatorship within a museum context, and to engender discussions around the multifarious ways in which objects might be re-considered, re-contextualised, and re-interpreted for the benefit of and in line with the interests of a broad, contemporary public. What follows is a summary of the conceptual considerations and questions that underpinned the workshop explorations the Museum devised for four distinct display contexts: the Bellerive Room, the Permanent Collection Gallery, and two temporary exhibitions on show at the time: ‘Emperors and Jewels – Treasures of the Indian Courts from the Al-Sabah Collection, Kuwait’ and ‘Transforming Traditions,’ an exploration of the arts ofnineteenth-century Iran.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.026 | 0.022 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".