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Record W4322004826 · doi:10.5194/egusphere-egu23-8658

The Virtual Water Gallery: Changing Attitudes through Art

2023· preprint· en· W4322004826 on OpenAlexaffabout
Louise Arnal, Martyn Clark, Stacey Dumanski, Efthimia Kosmas, John W. Pomeroy, Corinne J. Schuster‐Wallace

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
Fundersnot available
KeywordsExhibitionClimate changeIndigenousSociologyPolitical scienceVisual artsArtEcology

Abstract

fetched live from OpenAlex

Water is life. Water-related challenges, such as droughts, floods, wildfires, water quality degradation, permafrost thaw and glacier melt, exacerbated by climate change, affect everyone. Yet, it is challenging to communicate science on difficult, highly volatile topics such as water and climate change. Conceptualizing water-related environmental and social issues in novel ways, with engagement between diverse audiences may lead to comprehensive solutions to these complex challenges. Art can be a catalyst in the co-creation of new knowledge for the benefit of society.The Virtual Water Gallery (VWG) is a transdisciplinary science and art project of the Global Water Futures (GWF) program. Launched in 2020, the VWG aims to provide a collaborative space for dialogues between water experts, artists, and the wider public, to explore water challenges. As part of this project, 13 artists representing women’s, men’s and Indigenous voices across Canada were paired with teams of GWF scientists to co-explore specific water challenges in various Canadian ecoregions and communities. These collaborations led to the co-creation of artworks exhibited online on the VWG (www.virtualwatergallery.ca) in 2021.The VWG recently came to life in 2022 with an in-person exhibition in Canmore, Alberta, Canada. Surveys were developed to capture changes in perspectives regarding climate change and water challenges through this art-science exhibit. Participants of the VWG (artists and scientists), visitors to the online gallery, and visitors to the in-person exhibition in Canmore were all invited to take part in those surveys. The preliminary results from the surveys suggest that participants experienced changes in behaviour regarding water-related climate change mitigation, and that the degree of change depends on factors such as age, income and lived experience (i.e., floods and droughts). The results help elucidate how art viewers engage with art based on science and how science messages can be more effectively communicated through art.

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)0.006
metaresearch head score (Gemma)0.010
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 score0.021
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.001
Science and technology studies0.0160.018
Scholarly communication0.0180.010
Open science0.0020.020
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0210.002

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 head0.035
GPT teacher head0.244
Teacher spread0.209 · 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
Published2023
Admission routes2
Has abstractyes

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