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Record W2301993794

Cybersemiotics: Why Information Is Not Enough (Toronto Studies in Semiotics and Communication)

2008· book· en· W2301993794 on OpenAlexaboutno aff
Sren Brier

Bibliographic record

VenueUniversity of Toronto Press eBooks · 2008
Typebook
Languageen
FieldComputer Science
TopicSemantic Web and Ontologies
Canadian institutionsnot available
Fundersnot available
KeywordsSemioticsAutopoiesisEpistemologyCyberneticsBiosemioticsSociologySemiosisInformation scienceCognitive scienceComputer scienceSocial sciencePsychologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

A growing field of inquiry, biosemiotics is a theory of cognition and communication that unites the living and the cultural world. What is missing from this theory, however, is the unification of the information and computational realms of the non-living natural and technical world. Cybersemiotics provides such a framework.By integrating cybernetic information theory into the unique semiotic framework of C. S. Peirce, Sren Brier attempts to find a unified conceptual frame work encompassing the complex area of information, cognition, and communication science. The integration is performed through Niklas Luhmann?s autopoietic systems theory of social communication. The link between cybernetics and semiotics is further an ethological and evolutionary theory of embodiment combined with Lakoff and Johnson?s ?philosophy in the flesh.? This demands the development of a transdisciplinary philosophy of knowledge: as common sense as well as it is cultured in the humanities and the sciences. Such an epistemologica l and ontological frame work is also developed in the book.Cybersemiotics not only builds a bridge between science and culture, but it also provides at framework encompassing them both. The Cyber-semiotic framework offers a platform for a new level of global dialogue between knowledge systems including a view of science that does not compete with religion but offers the possibility for mutual and fruitful exchange.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.753
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.043
GPT teacher head0.246
Teacher spread0.203 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations13
Published2008
Admission routes1
Has abstractyes

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