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Record W2787791500 · doi:10.36510/learnland.v11i1.919

An Exploration of Artistic and Technological Symmetry

2018· article· en· W2787791500 on OpenAlex

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueLEARNing Landscapes · 2018
Typearticle
Languageen
FieldPsychology
TopicScience Education and Perceptions
Canadian institutionsnot available
Fundersnot available
KeywordsCoding (social sciences)Computer scienceComputational thinkingHeading (navigation)Point (geometry)Reading (process)SoftwareVisual artsMathematics educationHuman–computer interactionArtificial intelligencePsychologySociologyArtMathematicsProgramming languageGeometryEngineeringLinguisticsPhilosophySocial science

Abstract

fetched live from OpenAlex


 
 
 In this interview, biologist, artist, and shiatsu healer Artemis Papert describes how computational thinking can help people organize their thoughts in a more formal way. She discusses TurtleArt, a software that allows both children and adults to create two-dimensional static art images using geometry and coding as a medium. TurtleArt not only bridges the worlds of math and art, but is also easy to learn. She concludes by reading an excerpt from the article, “Teaching Children Thinking”— written in 1971 by her father Seymour Papert—as a still relevant starting point for where technology is heading.
 
 

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.375
Threshold uncertainty score0.999

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)0.0020.000

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 head0.062
GPT teacher head0.376
Teacher spread0.314 · 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