Bibliographic record
Abstract
Holocaust education is as vital as it is global in scope. However, museums cannot simply present the uninterpreted, vivid trauma of the Holocaust to young children. This challenge is then further complicated as museums must make the learning enjoyable enough that children want to learn it—a seemingly impossible task. To avoid Holocaust fatigue or traumatizing young audiences, I suggest here a triad model with which museum professionals should engage to create a meaningful and educational Holocaust exhibit for children. The triad model is based on participant agency, authenticity, and personal connection and can be seen in examples worldwide. In this article, I will focus on three main exemplars and specifically outline how they include each element of the proposed triad conceptual model in their exhibitions. To further illustrate its importance, I will close with a brief direct comparison to one recent Holocaust exhibit that does not engage fully with all the elements of the triad model and thus is a missed opportunity for youth participants.
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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.016 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".