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Record W4254753005 · doi:10.22215/etd/2021-14365

The White Settler Colonial Landscape of Toronto's Wychwood Park

2021· dissertation· en· W4254753005 on OpenAlexaffabout
Emily R.M. Lind

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsCarleton UniversityRoyal Ontario Museum
Fundersnot available
KeywordsColonialismWhite (mutation)The artsRacismSociologyLandscape designGender studiesGeographyArtVisual artsArchaeology

Abstract

fetched live from OpenAlex

Mythologized as a former artist's colony, Wychwood Park is a gated community in midtown Toronto that encompasses fifty-eight homes built at the turn of the twentieth century.Wychwood Park's landscape plan is one of Canada's earliest examples of a garden suburb -a suburban design model derived from the turn-of-the-twentieth-century English Garden City movement.The Park boasts the highest concentration of Arts and Crafts domestic architecture in Toronto.Famous early residents included artists and art patrons who were instrumental in establishing what became the Art Gallery of Ontario, the Royal Ontario Museum, the Ontario College of Art and Design, and the Ontario Society of Artists.In this dissertation, I argue that Wychwood Park is a white settler colonial landscape.This argument is informed by the idea of landscape as an actor in social and political processes, rather than a reflection of them.The physical landscape of Wychwood Park, and the extent to which it reflects the ideas and values that sustain settler colonial rule, are seriously interrogated in this project.I am interested in the ways that a neighbourhood like Wychwood Park can teach Torontonians something about how patriarchy and racism work and what it means to live in an environment shaped by gendered/racialized thinking and social organization.I am informed by Richard Schein's contentions that "discourses of racialized social relations work through landscapes" 1 and that landscapes are the sites in which racialized discourses become "materialized." 2 In this 1 Richard Schein, "A Methodological Framework for Interpreting Ordinary Landscapes: Lexington, Kentucky's Courthouse Square," Geographical Review 99, no. 3 (2009): 396. 2 Richard Schein, "The Place of Landscape: A Conceptual Framework for Interpreting an American Scene," Annals of the Association of American Geographers 87, no. 4 (1997): 666.Completing this degree took nearly thirteen years, and in that time I was encouraged and mentored by countless people -many of whom are still in my life, some of whom are not.My sincere gratitude to my former partner, Michael Franklin, who listened enthusiastically and lovingly through countless iterations of the ideas that finally took shape in this thesis.My former best friend, Claire L. Carter, was similarly unrelenting in her belief in my talent and promise as a scholar.I carry both of their love with me always.I was accompanied by fabulous colleagues and friends in Cultural Mediations, and the long conversations, cheap beer, and seminar workshops I shared with Egemen Ozbek, Jason Green, Owen Lyons, Nicholette Prince, and Bianca Briciu broke the isolation of graduate study and moved my thinking in directions I wouldn't have encountered otherwise.Helin Burkay also became a cherished friend and I continue to learn from her every time we speak.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.046
Threshold uncertainty score0.336

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0180.007
Scholarly communication0.0050.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.001

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.

Opus teacher head0.006
GPT teacher head0.247
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2021
Admission routes2
Has abstractyes

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