Bibliographic record
Abstract
In this chapter, I provide my reflections on designing Crossroads of Continents: Cultures of Siberia & Alaska , an exhibition that opened at the National Museum of Natural History, Smithsonian Institution in 1988. Crossroads addressed the cultural diversity, similarities, and contacts among eight ethnic groups living on the lands and islands surrounding the North Pacific: four from Siberia – Chukchi, Koryak, Even, and Peoples of the Amur River – and four from Alaska – Inuit, Aleut, Tlingit, and Northern Athabaskans. This massive travelling exhibition, created in the 1980s, combined collections from North American and Soviet museums. It was the first such collaborative museum effort as the icy distancing of the Cold War was beginning to thaw. As I reflect on my personal and professional experiences, I consider the emotional experience of the designer, as well as the challenges, processes, and practices involved in such a project. I highlight the labour and shared responsibilities and the material and intellectual trials involved in creating exhibitions, as well as the role of the design consultancy in museum practice. Though Crossroads closed over 30 years ago, perhaps this recounting will stimulate and inform future projects and their makers.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.063 | 0.017 |
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".