Contemporary Presents: The Canadian War Museum’s <i>Afghanistan</i>—A Glimpse of War and the Unfinished Business of Representation
Bibliographic record
Abstract
As an exhibition organized and presented by a national cultural institution whose mandate is to educate the public on the reasons, reactions, mechanisms and impacts of war, Afghanistan: A Glimpse of War at the Canadian War Museum had the opportunity to address the conflict that has shaped contemporary Afghanistan and the nature of the current war in which Canada is an active participant. As such, the appearance and effect of this exhibition must be evaluated not only in terms of its place in relation to historical and archival records, but also in terms of the knowledge and perceptions it generated in the present. I attend to the choice of objects and to the narrative they introduce, and question the institutional claim to an apolitical and elliptical exhibition strategy. While a museum exhibition can never bring the totality of the subject to which its artifacts and objects refer into the space of representation, it is nonetheless the cumulative result of a set of decisions, practices and strategies that are directed towards a specific end. I investigate the effects that the idea of “contemporary history” had on the exhibition as a whole, TOPIA 20 94 and ask whether the subject of the exhibition would have been better addressed as a contemporary present.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 0.001 |
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".