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Record W1529291223 · doi:10.7202/1062361ar

In Praise of the Garrison Mentality: Why Fear and Retreat May be Useful Responses in an Era of Climate Change

2019· article· en· W1529291223 on OpenAlexaffvenueabout
Sherrie Malisch

Bibliographic record

VenueStudies in Canadian Literature · 2019
Typearticle
Languageen
FieldArts and Humanities
TopicEcocriticism and Environmental Literature
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPraiseCriticismEnvironmental ethicsHumanityEcocriticismReading (process)AestheticsIsolation (microbiology)Climate changeHistoryPsychologySociologyLiteratureSocial psychologyEcologyLawPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

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?”

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.755
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.278
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2019
Admission routes3
Has abstractyes

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