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Record W3152678037 · doi:10.7202/1076193ar

Boundary Conditions: Crossing Spatial Boundaries as a Matter of Mind

2021· article· en· W3152678037 on OpenAlexvenueno aff
Judith van der Elst

Bibliographic record

VenueRecherches sémiotiques · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLanguage and cultural evolution
Canadian institutionsnot available
Fundersnot available
KeywordsBiosemioticsEmbodied cognitionCognitive scienceBoundary (topology)EpistemologyPerceptionKey (lock)Point (geometry)Computer scienceSociologyCommunicationPsychologyPhilosophySemioticsMathematics

Abstract

fetched live from OpenAlex

A key step in understanding different ways of experiencing the world, consists in exploring the limits of the human mind and the languages we use to make sense of our surrounding worlds. The concept of boundary is central in this endeavor. When we think of a boundary in the broadest sense, we think of an entity (or event) demarcated from its surroundings. Whether these boundaries reflect the structure of the world or just the organizing activity of our mind is a matter of intense philosophical debate. In this paper, human spatial thinking is a starting point to further explore our interactions with and within our environment. I argue that biosemiotics offers the most suitable framework for doing so, as it integrates humans in the larger communication network flow. Yet the spatial aspect of communication has received only limited attention in the biosemiotic literature. Furthermore, basing myself on my recent crossover practice in art/science, I argue that an embodied-embedded approach is necessary to dissolve and redefine spatial categories, allowing the investigation and potential crossing of the boundaries of our perceptual worlds.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.602
Threshold uncertainty score0.998

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 studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.068
GPT teacher head0.394
Teacher spread0.326 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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