In Praise of the Garrison Mentality: Why Fear and Retreat May be Useful Responses in an Era of Climate Change
Bibliographic record
Abstract
This essay revisits one of the foundational settler texts of Canadian literature, Northrop Frye’s “Conclusion” to the Literary History of Canada. It offers a controversial re-reading of Northrop Frye’s infamous “garrison mentality” thesis from the perspective of contemporary eco-criticism, particularly in view of the global crisis of climate change. The essential ecological logic of Frye’s account is that human isolation from nature impedes humanity’s “fullest functioning as a species.” However, the logic of the garrison thesis has been implicitly shared by critics who purport to oppose Frye’s approach; at base, both Frye and his critics assume that human-nature interconnection fosters human potential and creativity. Drawing on a number of prominent environmental biologists and ecocritics, the essay demonstrates that the garrison mentality, in which humans maintain a respectful distance from nature, may be the most ecologically sound response. This opens up a provocative question: “What if the most crucial role for literature . . . is not to fuel and thrive on the individual quest for creative fulfillment and self-understanding, but to harness itself to the task of bringing human aspirations, collectively, within limits?”
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.033 | 0.124 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 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".