Review of Dazhiikigaadeg Maanendamowin: Wanichigewin gaye Wiijiiwidiwin gii-ayaag COVID-19 / Transforming Grief: Loss & Togetherness in COVID-19 Exhibition at Fort York in Tkaronto/Toronto, Ontario, Canada, 24 March 2023 - 7 January 2024
Bibliographic record
Abstract
This viewpoint is a participatory reflection and response to the exhibition Dazhiikigaadeg Maanendamowin: Wanichigewin gaye Wiijiiwidiwin gii-ayaag COVID-19 / Transforming Grief: Loss & Togetherness in COVID-19, displayed at Fort York in Tkaronto/Toronto, Ontario, Canada, from March 2023 to January 2024. A graduate class from the University of Toronto visited the exhibition as part of the Winter 2023 ischool Information Management course ‘Museums, Archives and the Truth and Reconciliation Commission’, taught by Phillips. This piece includes observations and photographs from the students, as well as details of the process of creating and curating the exhibit from Armando Perla and Raven Spiratos, former-Curator for Toronto History Museums and exhibit curator (respectively). The content from the course discussions, readings, and assignments are put into conversation with this innovative community-based exhibition, giving students a rich understanding of ways to prioritize the needs of communities to activate decolonizing, Indigenizing, and new ways of thinking about museums, galleries, and archives.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".