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Record W4407068870 · doi:10.18192/clg-cgl.v8i2.7374

Arts Sector Research in Development

2025· article· en· W4407068870 on OpenAlex
Jamie Gamble, Robin Nelson

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
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 · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicCultural Industries and Urban Development
Canadian institutionsnot available
Fundersnot available
KeywordsThe artsPolitical scienceVisual artsArt

Abstract

fetched live from OpenAlex

Despite good intentions, academic research often reflects an extractive model and is not always seen as useful within the Canadian arts sector. Mass Culture is a non-profit organization that aims to bring together cultural workers and academics in support of collaborative research and better knowledge mobilization. To that end, their Research in Residence (RinR) initiative involved complex collaborations between the arts sector and academia to explore five applied research projects on a topic of shared importance to participants - that is, articulating the value of the arts through qualitative rather than quantitative measurements. To learn from the experimental research design, participants conducted a developmental evaluation with five lines of inquiry: benefits and effects, program design adaptations, values alignment, efficacy and potential, and knowledge mobilization and research engagement. The evaluation had three purposes: (1) to gather data and facilitate analysis of the key questions that the initiative was trying to understand; (2) to inform Mass Culture's implementation and adaptation of the initiative; and (3) to generate insights on principles and practices that could inform the design of future initiatives. This article considers the second and third purposes, outlining key lessons learned that shaped the initiative and/or should inform future projects.

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: Other · Consensus signal: none
Teacher disagreement score0.611
Threshold uncertainty score0.860

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 head0.090
GPT teacher head0.362
Teacher spread0.273 · 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