Bibliographic record
Abstract
Abstract This article revolves in essence around the contributions made by the architect Moshe Safdie to the Yad Vashem memorial and museum in Jerusalem. Both probably need at least a brief introduction, if for no other reason than the nature of the present publication, which has a somewhat different scope than the type of art-historical or architectural-historical journals to which reflections of this kind are usually consigned. The first part draws a profile of Safdie, who enjoys a well-established international reputation, even if he has not yet been fully acknowledged in Italy. In order to better understand who he is, we shall focus on the initial phase of his career, up to 1967, and his multiple ties to Israel. The range of projects discussed includes the Habitat 67 complex in Montreal and a significant number of works devised for various contexts within the Jewish state. The second part focuses on the memorial and museum complex in Jerusalem that is usually referred to as Yad Vashem. We will trace Yad Vashem from its conception, to its developments between the 1950s and 1970s, up until the interventions of Safdie himself. Safdie has in fact been deeply and extensively involved with Yad Vashem. It is exactly to this architect that a good share of the current appearance of this important institute is due. Through the analysis of three specific contributions – the Children’s Memorial, the Cattle Car Memorial and the Holocaust History Museum – and a consideration of the broader context, this article shows that Yad Vashem is today, also and especially thanks to Safdie, a key element in the formation of the identity of the state of Israel from 1967 up until our present time.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".