Art for a N[ot]ation: An Ethics of Curating the Group of Seven and Their Contemporaries
Bibliographic record
Abstract
The familiar and fabled Canadian group of landscape painters known as the Group of Seven and their contemporaries hold a commanding space in a certain national cultural memory. Their legacies are steadily being reconsidered by scholars and curators of Canadian historical art today. This paper deepens the conversations around ethical curating of these canonical Canadian artworks from a settler curator’s perspective. It considers the leading narratives about the Group of Seven, the institutions that supported them, and the exhibitions, programs, and texts that mythologized them. As part of a larger project in research-creation this paper takes an empathic position of not-knowing to responsibly produce an ethical standard for curators of today to proceed in their practices. It does so through a personal investigation of curatorial practice and relationships to modernist Canadian landscape painting by curator Will Boyle who is actively curating an adjacent exhibition called Art for a N[ot]ation (2021). This text presents a series of important moments in the story of the Group of Seven and considers the role of the curator in each rendition. It presents the leading literature on both curatorial methodologies and those curatorial decisions that concern the Group of Seven and other practicing landscape artists of the time. It presents these critical writings in relation to these important moments and meditates on their effect today. It does a deep critical analysis of three fiercely different current and recent exhibitions that in some capacity deal with the legacy of these painters. It does these things to inform the conjunctive exhibition and create a space so that exhibitions of our time can ethically respond to dominant Canadian art histories.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.065 | 0.088 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".