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Complexity, Systems Thinking and an Integrated Systems Engineering and Project Management Model

2020· article· en· W3089679234 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

VenueINCOSE International Symposium · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsNova Scotia Department of Agriculture
Fundersnot available
KeywordsAgile software developmentComputer scienceComplexity managementSystems thinkingProcess (computing)Management scienceProcess managementKey (lock)Project managementSystems engineeringProduct (mathematics)Knowledge managementEngineering managementEngineeringSoftware engineeringArtificial intelligenceBusiness

Abstract

fetched live from OpenAlex

Abstract Although theory and guiding principles exist for the integration of systems engineering and project management, there does not appear to be a practical approach offered. With unproductive tension, discipline‐specific disparate processes and models, and persistent project failures, there is a need for a paradigm shift in the approach to this integration. This shift may be achieved through systems thinking and the use of an integrated management model that includes key linkages, a decision support system and system dynamics. The model presented in the current study provides a structured approach for multiple disciplines to address and manage product and project complexity through cross‐functional processes within an interactive dynamic model environment consisting of system, process and policy levers. The model is validated through application of a case study, literature review, surveys and interviews with industry experts. Use of the model provides for critical thinking and a multi‐disciplinary agile approach to help navigate complexity.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.776
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
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 head0.028
GPT teacher head0.231
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