Planting the Nation: Tree Planting Art and the Endurance of Canadian Nationalism
Bibliographic record
Abstract
Planting trees under a piece-rate wage scheme is widely recognized in Canada as a veritable national “rite of passage” for young,White, middle-class university students and travelers. Canadian artists Sarah Ann Johnson, Lorraine Gilbert, and Althea Thauberger have received popular and critical acclaim for their artistic representations of the “tree planting experience” in Canada. In this article, the authors critically examine tree planting art—and its reception—and argue that it constitutes the most recent incarnation of art that links nature and nationalism together in the Canadian context. Following Catriona Sandilands incisive reflections on nature and nationalism in Canada, it is argued that the artists in question, and their various commentators, enshrine tree planting as an obligatory passage point through which White middle-class subjects can access both the “pioneering” moments of the nation and the promised greener tomorrow of Canada’s future. The connections made by the artists between nature and the nation are by no means innocent, as the authors aim to suggest, but rather, rely on a liberal-individualist account of labor in which the social dynamics of gender, class, and race are erased.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.042 | 0.029 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".