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Record W4239926455 · doi:10.1162/leon_a_01641

<i>Inhabitat</i>: An Imaginary Ecosystem in a Children’s Science Museum

2018· article· en· W4239926455 on OpenAlexaff
Haru Hyunkyung Ji, Graham Wakefield

Bibliographic record

VenueLeonardo · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsYork UniversityOntario College of Art and Design
Fundersnot available
KeywordsThe ImaginaryAgency (philosophy)Visual artsProjection (relational algebra)ArtInterconnectivitySociologyComputer scienceMedia studiesHuman–computer interactionPsychologySocial sciencePsychoanalysis

Abstract

fetched live from OpenAlex

Inhabitat is a mixed-reality artwork in which participants become part of an imaginary ecology through three simultaneous perspectives of scale and agency; three distinct ways to see with other eyes. This imaginary world was exhibited at a children’s science museum for five months, using an interactive projection-augmented sculpture, a large screen and speaker array, and a virtual reality head-mounted display. This paper documents the work’s motivations and design contributions, along with accounts of visitors’ playful engagements and reflections within the complex interconnectivity of an artificial nature.

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: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0060.008
Scholarly communication0.0050.003
Open science0.0010.008
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.015
GPT teacher head0.236
Teacher spread0.221 · 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

Citations1
Published2018
Admission routes1
Has abstractyes

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