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Record W4391300738 · doi:10.18192/clg-cgl.v8i1.6967

Artists Embedded in Government: Expanding the Cultural Policy Toolkit

2023· article· en· W4391300738 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCulture and Local Governance · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Artists have long worked in fields that are not related to art, instigating innovative ways of working in different institutional contexts from health to business to technology. Civic systems are no exception, with artists spearheading new ways of operating within government agencies. Some artists work covertly, bringing creative methods to traditional civic roles, while others are invited into government agencies in temporary positions as artists in residence addressing specific concerns. As local governments are increasingly challenged to provide services and operate equitably amid eroding public trust, opportunities for cross-sector collaboration uniting artists with government staff are compelling mechanisms for them to cocreate the necessary conditions for systemic change. The research reported herein explores how artists are engaged in cross-sectoral collaborative models of cultural policy within local governments. Governments already recognize the potential of formal artist residency programs conducted over set periods of time to advance civic goals. In addition, artists have been engaged in this work through informal government partnerships in departments including transportation, parks, and public health. Some collaborations act as applied research enacted internally, bringing more complex understandings of government operations, while others become deep processes of external engagement to expand awareness of local concerns. This paper presents a framework categorizing the structures in which artists work within government agencies to advance civic goals. The framework is based on research conducted on artists who were embedded in the government across the US from 2020 through 2022. Describing these structures highlights new ways of working within local government that center artists as agents that promote change; this paper lays the foundation for understanding how they operate and delineates opportunities and challenges for the artists and the governments that initiate collaboration. The framework is a foundation for cultural policy makers to evaluate artist in residence in government programs as a cultural policy tool and enable evaluation of the impact of their implementation.

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.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.237
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.028
GPT teacher head0.309
Teacher spread0.281 · 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