Ivan KARP et Steven D. LAVINE, éditeurs, Exhibiting Cultures: The Poetics and Politics of Museum Display, Washington et Londres, Smithsonian Institution Press, publié en collaboration avec l’American Association of Museums, 1991, 468 pages, illustré
Bibliographic record
Abstract
Pointe-à-Callière, a young Museum rising above the site of the founding of Montréal, first opened its doors on May 17, 1992. Its permanent exhibition of more than 4,000 m allows visitors to examine architectural remuants, archaeological artifacts and an 18th-century heritage building. The Museum's goal is to bring the history of Montréal alive and to illustrateit in an entertaining way. Visitors roam among authentic remuants testifying to the successive inhabitants of this site: Indians, French, British, North Americans and Quebeckers. A tour of the Museum, alone, as a family or with an interpreter-guide, is a chance to discover Montréal through its archaeological heritage. It also leads us to reflect on our own role in the way the past is preserved. Finally, it makes us think about how the traces we in turn leave behind will be tomorrow's heritage for the generations to come.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".