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Record W4252472321 · doi:10.1162/leon_a_01283

Perceptual Cells: James Turrell’s Vision Machines Between Two Paracinemas

2016· article· en· W4252472321 on OpenAlex
Alla Gadassik

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

VenueLeonardo · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCinema and Media Studies
Canadian institutionsEmily Carr University of Art and Design
Fundersnot available
KeywordsPerceptionMovie theaterArchitectureProjection (relational algebra)Perceptual systemCognitive scienceComputer scienceVisual artsPsychologyAestheticsCognitive psychologyComputer visionArtificial intelligenceArtNeuroscience

Abstract

fetched live from OpenAlex

James Turrell’s perceptual cells incorporate the neurophysiological apparatus as an active participant not only in the reception of projected moving-images, but also in the very production and transmission of virtual moving-images. Combining two perceptual phenomena—the stroboscopic effect and the Ganzfeld Effect—Turrell’s perceptual cells integrate the architecture of projection with the architecture of organic vision to produce a single networked extra-sensory medium. This paper performs a phenomenological analysis of Turrell’s Light Reignfall (2011) perceptual cell, following its design, effects on the viewer, and cultural and material history. In the process, the paper situates the perceptual cell between the history of avant-garde cinema (what historians have called “paracinema”) and the history of perceptual psychology and parapsychology (what the author terms “para-cinema”). Between these two paracinemas, Turrell’s perceptual cells activate the aesthetic potential of what the author discusses as “edgeless projection.”

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.028
GPT teacher head0.254
Teacher spread0.226 · 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