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Record W3089115302 · doi:10.15353/jirr.v3.1683

“Batavia”: An Analysis on the Pedagogical Possibilities and Limitations of Virtual Reality Art

2020· article· en· W3089115302 on OpenAlexaffvenue
Anand Sergeant

Bibliographic record

VenueJournal of integrative research & reflection · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicMuseums and Cultural Heritage
Canadian institutionsMcMaster University
Fundersnot available
KeywordsVirtual realityPoliticsNarrativeRepresentation (politics)Emerging technologiesSociologyArt methodologyAestheticsContemporary artEngineering ethicsEpistemologyPolitical scienceComputer scienceArtHuman–computer interactionEngineeringLiterature

Abstract

fetched live from OpenAlex

Publicly displayed art has long been an important mechanism for public pedagogy, historical representation, and critical thought. Thus, as art-creation technologies evolve enabling public artistic representations to change forms, it is important to critically examine the pedagogical and social implications of these novel art technologies. In this paper, I will analyze the pedagogical possibilities and the potential socio-political implications of an increasingly popular form of modern art representation: Virtual Reality (VR) art. Specifically, I argue that while the immersive and engaging form of VR technologies may offer some interesting possibilities as an educational practice for history through art, if they are not used properly, VR-art technologies may serve to propagate colonial narratives and inhibit a critical lens on historical events. Going forward, then, the ways in which novel artistic technologies are put into practice must be more critically examined and critiqued before they are launched into the public sphere.

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 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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.488
GPT teacher head0.460
Teacher spread0.028 · 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 teacher head, 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

Citations3
Published2020
Admission routes2
Has abstractyes

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