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Record W4410632539 · doi:10.22215/etd/2024-16491

Land, Science and Architecture: Politics of Scale in 1856–1939 Ottawa, Canada

2024· dissertation· en· W4410632539 on OpenAlexaboutno aff
Émélie Desrochers-Turgeon

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldArts and Humanities
TopicLandscape and Cultural Studies
Canadian institutionsnot available
Fundersnot available
KeywordsArchitecturePoliticsScale (ratio)GeographyPolitical scienceArchaeologyCartographyLaw

Abstract

fetched live from OpenAlex

Settler colonial regimes of city making in Ottawa have incorporated the built environment to construct a narrative of liberalism, benevolence, and rational governance, effectively obscuring the processes of land dispossession and environmental transformation. This dissertation investigates the land representations that shape Ottawa as a settler state capital, examining the scientific institutions of the Dominion Observatory, the Central Experimental Farm, the Geological Survey of Canada, and the Central Canada Exhibition at the turn of the twentieth century. It explores how these state institutions relied on the manipulation of scales and the construction of architectural fictions to alter land into metrics of possession. This dissertation historicizes and critically examines architecture’s entanglement with imperial networks and settler colonial imaginaries through practices of bordering, inventorying, improving, and displaying in Ottawa and across Canada. It argues that architectural expertise, coupled with centralized government control, constructed geographies that structured the lives of both human and non-human entities within imperial frameworks. Beyond the visual culture of science in Ottawa, this study explores the frictions and contradictions inherent in the negotiation of terrains through architecture. By considering scale both as a subject of study and as a methodological tool, it delves into architectural histories of land, highlighting agential materialities within these practices.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.294

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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 designNot applicable
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

Citations0
Published2024
Admission routes1
Has abstractyes

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