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Record W4249508888 · doi:10.1386/macp.11.2.225_1

Rent: Constructing community

2015· article· en· W4249508888 on OpenAlexaff
Kristen Smith

Bibliographic record

VenueInternational Journal of Media and Cultural Politics · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicFoucault, Power, and Ethics
Canadian institutionsYork University
Fundersnot available
KeywordsIdeologyGentrificationSociologyPower (physics)Community organizationTransformative learningPolitical economyGender studiesPolitical sciencePublic relationsLawEconomic growthPoliticsEconomics

Abstract

fetched live from OpenAlex

Abstract Can a community – a culture – produce change and evidence ‘transformative practice’? This paper investigates the process by which marginalized individuals incite change through the means of language within their cultural communities. The musical Rent is the case study. In Community: Pursuing the Dream, Living the Reality, Suzanne Keller reveals recurrent elements of community: communities have shared territory, ideals, allegiances, and collective frameworks. All of these elements of community are featured in Rent. In Rent, there are three prominent manifestations of community: the AIDS Community, New York City Community, and America as Community. Each of these three manifestations evidence Michel Foucault’s three power struggles. Rent demonstrates the struggle against domination that the AIDS community faces as a result of being marginalized and disenfranchised. Additionally, Rent exposes the struggle against exploitation of residents during gentrification of the Lower East Side of New York City. Furthermore, Rent evidences America’s attempt and failure at constructing a community, subjecting its citizens to a dominant capitalist society and forcing its citizens into submission. Ultimately, Rent challenges America’s dominant ideology through the creation of a counter-discourse. The very act of challenging a dominant ideology is a powerful act. Rent evidences that community constructed through creativity and defined by love can inspire change.

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)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.339

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.123
GPT teacher head0.405
Teacher spread0.282 · 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 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
Published2015
Admission routes1
Has abstractyes

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