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Record W4402356442 · doi:10.22323/2.23060801

Creating resonance with arts-based approaches to sustainability science communication

2024· article· en· W4402356442 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.

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

Bibliographic record

VenueJournal of Science Communication · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicClimate Change Communication and Perception
Canadian institutionsPrivy Council Office
FundersNovo Nordisk
KeywordsThe artsMainstreamSustainabilityConstructiveAffectionSociologyEngineering ethicsPsychologyPolitical scienceComputer scienceVisual artsEngineeringArtSocial psychologyProcess (computing)Ecology

Abstract

fetched live from OpenAlex

Mainstream science communication has struggled to drive sustainability changes. We experimented with arts-based methods in a workshop series that sought to co-create new methods and formats for sustainability science communication with communicators, artists, scientists, and policy-makers. Here, we describe how we used Hartmut Rosa’s notion of resonance to interrogate our experiences, prompted by the workshops and the artwork produced in them. We show how the elements of resonance: affection, emotion, transformation and uncontrollability, fundamentally reshaped the workshops in constructive ways that we could not have predicted. We conclude by drawing out three insights for science communication practice.

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)0.016
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.404
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0160.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0040.007
Scholarly communication0.0010.003
Open science0.0030.000
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 head0.557
GPT teacher head0.490
Teacher spread0.067 · 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