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Record W4225473256 · doi:10.5281/zenodo.10576385

Dark Matter: An Ecopsychological Approach to the Ontology of Plant Expression in Charlie Kaufman's Adaptation and Richard Linklater's A Scanner Darkly

2021· article· en· W4225473256 on OpenAlexaff
David M. J. Carruthers

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarth Systems and Cosmic Evolution
Canadian institutionsQueen's University
Fundersnot available
KeywordsAdaptation (eye)ScannerExpression (computer science)OntologyCognitive sciencePsychologyArtComputer sciencePhilosophyNeuroscienceEpistemologyArtificial intelligenceProgramming language

Abstract

fetched live from OpenAlex

Taking up Michael Marder’s “object of psychoanalysis, wherein we might detect a vegetalapproach to the psyche,” and Timothy Morton’s dark ecology, which traces thetwisted loops of agrilogistics, this article proposes an ecopsychological approach to theexpression of plant soul as the very constitution of human subjectivity. Examining RichardLinklater’s adaptation of Philip K. Dick’s A Scanner Darkly, which demonstrates the prettyblue Mors ontologica’s insidious plant agency to cleave the somatic human spirit, and CharlieKaufman’s Adaptation, wherein cinematic plant-thinking demands temporal distortionsthat render the human uncanny, this article positions the plant as the primary mover, theanimating force and manifestation of human desire and its expression.

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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.029
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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 head0.205
GPT teacher head0.443
Teacher spread0.239 · 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 designTheoretical or conceptual
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
Published2021
Admission routes1
Has abstractyes

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