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Record W2034396927 · doi:10.1080/0966369x.2011.624590

Gay in a ‘government town’: the settlement and regulation of gay-identified men in Ottawa, Canada

2011· article· en· W2034396927 on OpenAlexaffabout
Nathaniel M. Lewis

Bibliographic record

VenueGender Place & Culture · 2011
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsQueen's University
Fundersnot available
KeywordsGovernmentalityLesbianPoliticsGender studiesHomosexualitySociologyGovernment (linguistics)Human sexualityPolitical scienceLaw

Abstract

fetched live from OpenAlex

This case study examines Ottawa, Canada, a ‘government town’, as both a destination for mobile gay men and a place where their conduct historically has been regulated by the government and military institutions located there. By placing the findings of 24 in-depth qualitative interviews with self-identified gay men in a Foucauldian governmentality framework, I argue that the government town is a powerful attractor for gay men in terms of economic opportunity and official prescriptions of nondiscrimination and acceptance, but is also a site where gay men and gay communities are regulated into certain modes of conduct. In particular, this article finds that Ottawa, as both a historic center of antigay activity and a more recent center of an LGBT (lesbian, gay, bisexual, transgendered) rights-seeking agenda in Canada, encourages practices that are based on discretion, gender normalization, and maintenance of the status quo. The article argues that these practices – with some notable exceptions – have led to a fragmented gay community characterized by economic and professional stratification, out-of-town consumption of gay culture, and a lack of recognizable social, political, and geographic focal points for gay men. It also posits that the mechanisms through which governmentality is leveraged are particularly central to the experiences of sexual minorities in places like Ottawa, where government institutions are especially dense or thick.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.771

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)0.0010.000

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 head0.045
GPT teacher head0.300
Teacher spread0.255 · 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 designObservational
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

Citations21
Published2011
Admission routes2
Has abstractyes

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