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Record W4232506134 · doi:10.3138/uhr.47.1-2.03

Taming the Jungle in the City: Uprooting Trees, Bushes, and Disorder from Mount Royal Park

2018· article· en· W4232506134 on OpenAlexvenueaboutno aff
Matthieu Caron

Bibliographic record

VenueUrban History Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsJungleMountGovernment (linguistics)NewspaperGeographySociologyEcologyHistoryArchaeologyMedia studiesEngineering

Abstract

fetched live from OpenAlex

From the late 1940s to the early 1960s, Montreal’s obsession with regulating immoral behaviour led to several urban renewal schemes. This article looks at the municipal government’s decision to clear an overgrown section of Mount Royal Park nicknamed the “Jungle” and ultimately to reconstruct it as a heterosexual space. This area of the park was highly patrolled by police officers who viewed it as a gathering place for undesirable persons; newspapers highlighted how drunkards, criminals, sex maniacs, perverts, and, most importantly, homosexuals defiled the park’s character. To rid Mount Royal Park of its Jungle and those who had appropriated it, the city came up with a radical plan to simplify the police department’s techniques of surveillance: the ecological clearance of the Jungle. The clearcutting of the Jungle, a process known as the Morality Cuts, eroded the environmental and ecological character of Mount Royal, with the immediate repercussion of “balding” the park. However, in the aftermath, the mobilization of other civic actors, including civil servants and the Montreal Parks and Playgrounds Association, enabled a restorative strategy for the park’s ecology.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.758
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.026
GPT teacher head0.236
Teacher spread0.210 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2018
Admission routes2
Has abstractyes

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