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Defining wilderness: the evolution of Banff National Park

2023· article· en· W4388904396 on OpenAlexaffabout
Felix Mayer, Piper Bernbaum, Fabian Neuhaus, Natalie Robertson

Bibliographic record

VenueArchitecture_MPS · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsCarleton University
Fundersnot available
KeywordsWildernessNational parkGeographyNational identityTourismWilderness areaBoundary (topology)ExpansiveDestinationsCultural landscapeEnvironmental ethicsSociologyEthnologyArchaeologyPolitical scienceEcologyLawPolitics

Abstract

fetched live from OpenAlex

Internationally, Canada is a country known for its iconic, expansive landscapes. Images of the Rocky Mountains and destinations such as Lake Louise and Banff are instantly recognisable, drawing visitors from around the world each year. Wilderness is a term that has become irrevocably linked to Canadian national identity and Canadian culture. Nowhere is the significance of wilderness within Canadian culture and history more visible than in the country’s vast network of provincial and national parks. This article explores the history of Canada’s oldest national park, Banff, and the creation and evolution of its boundaries. It explores how park boundaries act as spatial tools to project legal frameworks and cultural values, creating landscapes and an experience of place rather than simply preserving existing conditions or ecologies. The history of Banff National Park is also used to explore the broader implications that idealised or romanticised notions of wild spaces have had in shaping Canadian cultural values, which in turn have shaped attitudes towards landscapes and the defining of landscapes into industrialised zones and zones of conservation. Fundamentally an architectural study of site, this article explores the evolution of the national park boundaries of Banff through their interactions with industrial interests, cultural landmarks and historical narratives, dissecting their capacities to control intensely layered and contested areas. Through a study of the park boundary and the forces that have shaped it over time, the dynamics of power, exclusion, exploitation and commercialisation inherent to the definition of landscapes and boundaries are investigated.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.018
GPT teacher head0.311
Teacher spread0.294 · 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 designTheoretical or conceptual
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

Citations1
Published2023
Admission routes2
Has abstractyes

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