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Record W2982180325 · doi:10.1002/sres.2629

A vision for advancing systems science as a foundation for the systems engineering and systems practice of the future

2019· article· en· W2982180325 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

VenueSystems Research and Behavioral Science · 2019
Typearticle
Languageen
FieldDecision Sciences
TopicComplex Systems and Decision Making
Canadian institutionsSurrey Place Centre
Fundersnot available
KeywordsReductionismSystems scienceComplex systemSystems thinkingDisciplineSystems theoryComplexity scienceEpistemologyComputer scienceManagement scienceMaturity (psychological)Engineering ethicsSociologyEngineeringPolitical scienceArtificial intelligenceSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

Abstract In this paper, I argue that the fragmented state and uneven maturity of current systems science will render it increasingly inadequate for meeting the future needs of the engineering and practice disciplines depending on it. I explain that it is not the case that System Science is a holistic discipline in contrast with the reductionism of classical science, but that Systems Science has both reductionistic and holistic dimensions, dealt with respectively by two “movements” within systems science, which I will designate as “Complexity Science” and “Systems Research”. I argue that in many situations the internal workings of a system can be satisfactorily addressed with the mainly reductionistic methods of Complexity Science, whereas when external factors play a significant role, the mainly holistic methods of Systems Research are brought to the fore. This suggest that Complexity Science and Systems Research are not really as disjunct as often portrayed, but represent special cases under a wider conception that would hold across a spectrum of ratios between ‘internal complexity’ and ‘external complexity’ of the system of interest, and that would entail a differential emphasis on reductionistic and holistic methods based on contextual factors. Such a wider conception could not only help to unify systems science, but would also support analysis and intervention in the ‘middle ground’ between these polar types. This is relevant for Systems Engineering and Practice because as the world's complexity grows engineers and practitioners will increasingly have to deal with situations that are complex both internally and externally. This suggests an increasingly urgent need for the development of the envisioned ‘wider conception’ of systems in which we can deal in an elegant and principled way with shifts in the balance between internal and external complexity. In this paper I propose that a scientific general theory of systems could provide such a wider conception, and that it could serve as a basis for the unification of systems science, provide support for the scientific maturation of the discipline, and extend the capability and utility of systems science in important ways. I present approaches and frameworks that would support the development of such a theory, present wide‐ranging evidence suggesting that we are in a favourable position for developing one, and indicate important areas to focus on in future research.

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)0.054
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.773
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0540.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.004
Science and technology studies0.0030.001
Scholarly communication0.0060.002
Open science0.0030.001
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 head0.183
GPT teacher head0.520
Teacher spread0.337 · 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