MétaCan
Menu
Back to cohort
Record W2326972309 · doi:10.1386/eta.8.3.349_7

Catch and release: Artworks inspiring insight into environmental issues

2012· article· en· W2326972309 on OpenAlexafffundabout
Ruth Beer, Kit Grauer

Bibliographic record

VenueInternational Journal of Education through Art · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsUniversity of British ColumbiaEmily Carr University of Art and Design
FundersParks Canada
KeywordsExhibitionContext (archaeology)Experiential learningDemiseCitizen journalismGovernment (linguistics)SustainabilityVisual artsPublic relationsSociologyPolitical scienceMedia studiesArtArchaeologyGeographyPedagogyEcology

Abstract

fetched live from OpenAlex

‘Catch+Release’ is a Canadian government-funded research and creation project of interactive new media artworks produced by a team of artists, educators and designers in collaboration with Parks Canada’s Gulf of Georgia Cannery National Historic Site. Its exhibition component addresses marine environments and coastal communities that once relied on the fishing industry. Through viewer engagement with the artworks, within the context of the museum, the exhibition fosters awareness of the region’s social history and contemporary cultural conditions – ‘catching’ stories and ‘releasing’ stories into the public sphere. The aesthetic and pedagogical strategies for promoting sensory, experiential, participatory learning opportunities and critical engagement, acknowledge the museum as an important informal educational site in its role as custodian, maker of meaning and source of regional identity. The exhibition’s themes resonate globally in coastal communities that share challenges in adapting to (g)local ci cumstances of cultural and geographic transitions due to the demise of fishing industries.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.018
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.009
Scholarly communication0.0080.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.024
GPT teacher head0.285
Teacher spread0.261 · 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

Citations6
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueInternational Journal of Education through ArtSame topicMuseums and Cultural HeritageFrench-language works237,207