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Record W1997780809 · doi:10.1108/03684920410556007

Second‐order cybernetics: an historical introduction

2004· article· en· W1997780809 on OpenAlexaff
Bernard Scott

Bibliographic record

VenueKybernetes · 2004
Typearticle
Languageen
FieldPhysics and Astronomy
TopicOrigins and Evolution of Life
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsCyberneticsEpistemologyPerspective (graphical)Computer scienceOrder (exchange)BiocyberneticsCognitive sciencePhilosophyArtificial intelligencePsychology

Abstract

fetched live from OpenAlex

In 1974, Heinz von Foerster articulated the distinction between a first‐ and second‐order cybernetics, as, respectively, the cybernetics of observed systems and the cybernetics of observing systems. Von Foerster's distinction, together with his own work on the epistemology of the observer, has been enormously influential on the work of a later generation of cyberneticians. It has provided an architecture for the discipline of cybernetics, one that, in true cybernetic spirit, provides order where previously there was variety and disorder. It has provided a foundation for the research programme that is second‐order cybernetics. However, as von Foerster himself makes clear, the distinction he articulated was imminent right from the outset in the thinking of the early cyberneticians, before, even, the name of their discipline had been coined. In this paper, the author gives a brief account of the developments in cybernetics that lead to von Foerster's making his distinction. As is the way of such narratives, it is but one perspective on a complex series of events. Not only is this account a personal perspective, it also includes some recollections of events that were observed and participated in at first hand.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.005
Science and technology studies0.0030.011
Scholarly communication0.0050.007
Open science0.0010.002
Research integrity0.0020.006
Insufficient payload (model declined to judge)0.0050.001

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 head0.008
GPT teacher head0.224
Teacher spread0.216 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations212
Published2004
Admission routes1
Has abstractyes

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