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Cultivating Research Through Digital Ecosystems

2017· article· en· W2742074799 on OpenAlex
Mary Hafeli, Juan Carlos Castro, Julia Marshall, Chris Grodoski

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueVisual Arts Research · 2017
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsConcordia University
Fundersnot available
KeywordsMediationCommissionSociologyFunction (biology)Diversity (politics)Space (punctuation)Digital ecosystemField (mathematics)Position (finance)Public relationsKnowledge managementPolitical scienceSocial scienceComputer scienceBusiness

Abstract

fetched live from OpenAlex

Abstract The research culture of art education is an ecosystem of ideas and inquiry. This ecosystem of research extends into the varied forms of digital mediation. Now in its fourth year, the National Art Education Association Research Commission’s objective is to cultivate, connect, and amplify art education research. In this essay, we theorize the analogy of research ecosystems and use the example of our Interactive Café as a space that fosters research culture. Digital forums such as the Interactive Café function as a place where individuals who produce and use research can interact and exchange ideas. Our position is that digital mediation needs to strengthen interdependence and vibrancy through spaces and events that connect a diversity of knowledge producers and stakeholders. For the Research Commission, research that is born digital is ripe with potential to connect, evolve, and amplify throughout the field.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.620
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0080.001
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.006

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 head0.522
GPT teacher head0.535
Teacher spread0.013 · 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