Bibliographic record
Abstract
Over the last thirty years museums around the world have shown an increased willingness to take on what is often characterized as ‘difficult subject matter.’ Absent in Anglophone museum studies literature, however, is a sustained discussion on what it is about such exhibitions that render them ‘difficult’ and, most important, what can be achieved by making painful histories public. This paper sets out to stimulate such discussion, illustrating the relevance of our concerns within the context of a comparative analysis of two recent Swedish exhibitions: The Museum of World Culture’s No Name Fever: AIDS in the Age of Globalization; and Kulturen’s Surviving: Voices from Ravensbrück. Very divergent in their presentation strategies and in the type of information presented, these exhibitions attempt to position their viewers in relation to violence and suffering of ‘others’ distant in time, place, or experience. We conclude by discussing the ways in which public history might animate a critical historical consciousness, a way of living with and within history as a never-ending question that constantly probes the adequacy of the ethical character and social arrangements of daily life.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.024 |
| Scholarly communication | 0.010 | 0.009 |
| Open science | 0.001 | 0.019 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.015 | 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".