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Record W66572124

The art of citizenship: mythmaking and neighbourhood change.

2009· dissertation· en· W66572124 on OpenAlexaboutno aff
Lynn Adam Saffery

Bibliographic record

VenueSummit (Simon Fraser University) · 2009
Typedissertation
Languageen
FieldSocial Sciences
TopicPublic Spaces through Art
Canadian institutionsnot available
Fundersnot available
KeywordsNeighbourhood (mathematics)CitizenshipPolitical scienceGeographyMathematicsLaw
DOInot available

Abstract

fetched live from OpenAlex

Community art is increasingly coming under scrutiny by urban leaders. Art contributes to vibrant communities, which often promotes economic vitality and liveability. Art is also a vehicle to express political and cultural beliefs. However, neighbourhoods with large artist populations often change as lower income residents gradually give way to elites attracted to urban beautification. How do artists respond to this contradiction? Do they agree that they are the “colonial arm of the conventional middle class” (Ley 2003)? I examine organizations and artists active on Commercial Drive, Vancouver to look at artists as both gentrifiers and social advocates. Through interviews and participant observation, I identify a framing discourse of artists trying to live a lifestyle that is critically aware, socially responsible and joyful. I argue that although artists promote change, they do not feel responsible for gentrification. Instead, they often resist gentrification and blame elites for negative community development.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.020
Threshold uncertainty score0.040

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.027
Scholarly communication0.0110.005
Open science0.0010.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.000

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 head0.021
GPT teacher head0.263
Teacher spread0.243 · 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
Published2009
Admission routes1
Has abstractyes

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