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Record W2279821515 · doi:10.1007/978-3-030-66073-4_11

Recovering the Gay Village: A Comparative Historical Geography of Urban Change and Planning in Toronto and Sydney

2021· book-chapter· en· W2279821515 on OpenAlexaffabout
Andrew Gorman‐Murray, Catherine J. Nash

Bibliographic record

Venue˜The œurban book series · 2021
Typebook-chapter
Languageen
FieldSocial Sciences
TopicUrban Planning and Governance
Canadian institutionsBrock University
Fundersnot available
KeywordsCommodificationMainstreamQueerPoliticsSociologyGender studiesSocial geographyConsumerismGeographyPolitical scienceSocial scienceHuman geographyEconomy

Abstract

fetched live from OpenAlex

Abstract This chapter argues that the historical geographies of Toronto’s Church and Wellesley Street district and Sydney’s Oxford Street gay villages are important in understanding ongoing contemporary transformations in both locations. LGBT and queer communities as well as mainstream interests argue that these gay villages are in some form of “decline” for various social, political, and economic reasons. Given their similar histories and geographies, our analysis considers how these historical geographies have both enabled and constrained how the respective gay villages respond to these challenges, opening up and closing down particular possibilities for alternative (and relational) geographies. While there are a number of ways to consider these historical geographies, we focus on three factors for analysis: post-World War II planning policies, the emergence of “city of neighborhoods” discourses, and the positioning of gay villages within neoliberal processes of commodification and consumerism. We conclude that these distinctive historical geographies offer a cogent set of understandings by providing suggestive explanations for how Toronto’s and Sydney’s gendered and sexual landscapes are being reorganized in distinctive ways, and offer some wider implications for urban planning and policy.

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: Other · Consensus signal: Other
Teacher disagreement score0.798
Threshold uncertainty score0.994

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 studies0.0000.001
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 head0.053
GPT teacher head0.272
Teacher spread0.219 · 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
GenreOther

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

Citations26
Published2021
Admission routes2
Has abstractyes

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