Bibliographic record
Abstract
The Museum of Vancouver (MOV) identifies reconciliation as one of the four pillars that guide its work. Reconciliation has become a matter of national significance in Canada since the release of the Truth and Reconciliation Report in 2008, which highlights the harmful legacies of residential schools on the daily lives of Indigenous Canadians. It also demonstrated that social inequalities continue to persist across the nation because of this, and other assimilationist policies previously adopted under Canada’s Indian Act. Recommendations of the report were aimed at improving Indigenous and non-Indigenous relations and removing barriers, both intentional and unconscious, that prevent Indigenous Canadians from accessing the same opportunities and services as other Canadians. It can take many years to implement institutional change, but public programming offers an opportunity to demonstrate intentions for change with more immediacy. This paper provides an overview of an art program created for Indigenous youth in the Greater Vancouver area by Indigenous professionals working in a museum setting. The initiative was funded through a creative partnership between the MOV and the City of Vancouver’s Green Infrastructure team and resulted in the creation of public art that was installed in a Green Infrastructure demonstration project within the city.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.048 | 0.012 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.002 |
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".