Curating Difficult Knowledge: Violent Pasts in Public Places
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
List of Illustrations List of Maps Acknowledgements Notes on Contributors Introduction: Witnesses to Witnessing E.Lehrer & C.E.Milton PART I: BEARING WITNESS BETWEEN MUSEUMS AND COMMUNITIES 'We were so far away': Exhibiting Inuit Oral Histories of Residential Schools H.Igloliorte The Past is a Dangerous Place: the Museum as a Safe Haven V.Szekeres Teaching Tolerance through Objects of Hatred: The Jim Crow Museum of Racist Memorabilia as 'Counter-Museum' M.E.Patterson Politics of the Past: Remembering the Rwandan Genocide at the Kigali Memorial Center A.Sodaro PART II: VISUALIZING THE PAST Living Historically through Photographs in Post-Apartheid South Africa: Reflections on Kliptown Museum, Soweto D.Newbury Showing and Telling: Photography Exhibitions in Israeli Discourses of Dissent T.Katriel Visualizing Apartheid: Re-framing Truth and Reconciliation through Contemporary South African Art E.Mosely PART III: MATERIALITY AND MEMORIAL CHALLENGES Points of No Return: Cultural Heritage and Counter-Memory in Post-Yugoslavia A.Herscher Defacing Memory: (Un)tying Peru's Memory Knots C.E.Milton (Mis)representations of the Jewish Past in Poland's Memoryscapes: Nationalism, Religion and Political Economies of Commemoration S.Kapralski Afterward: The Turn to Pedagogy: a Needed Conversation on the Practice of Curating Difficult Knowledge R.I.Simon Index
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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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