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Record W2887263813 · doi:10.1108/k-11-2017-0460

An evolutionary phenomenology of resilience

2018· article· en· W2887263813 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKybernetes · 2018
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsCarleton University
Fundersnot available
KeywordsCyberneticsOriginalityEpistemologyParliamentSociologyTransdisciplinaritySchema (genetic algorithms)Management scienceComputer sciencePoliticsKnowledge managementSocial scienceArtificial intelligenceLawPolitical scienceQualitative researchEngineering

Abstract

fetched live from OpenAlex

Purpose The purpose of the paper is to set out an evolutionary schema for organizational resilience using the established emergent autopoiesis coherence (EAC) framework, with empirical reference to the European Parliament’s development of institutional capacities since its foundation in 1952 as the Common Assembly of the European Coal and Steel Community (CA-ECSC). Design/methodology/approach The logic is categorical-synthetic and second-order cybernetic, implicitly underlain by a correspondence theory of truth united with a coherentism based in the epistemology of complex systems. Findings The European Parliament has constructed itself as a resilient organization, but the process has entailed over-learning of past lessons, creating behavioral syndromes of dysfunction in the face of new challenges. Research limitations/implications The work contrasts antifragility with resilience and suggests a new approach to it. Practical implications The analytical framework and conclusions hold value for the practical design of resilient organizations. Social implications The groundwork of the EAC’s conceptual framework is laid, and the basis for applying it to human and other naturally occurring societies is established. Originality/value K.W. Deutsch’s mid-twentieth century work on cybernetic-based learning in political systems is reconstructed, updated and applied to twenty-first century political phenomena. The insights are validated, and the analytical framework’s robustness is demonstrated.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.300
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.117
GPT teacher head0.414
Teacher spread0.297 · 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