The Systems Approach View from Professor Andrew P. Sage
Bibliographic record
Abstract
Andrew P. Sage is the Founding Dean Emeritus University Professor, and First American Bank Professor in the Systems Engineering and Operation Research Department at George Mason University in USA. Professor Sage is recognized as one of the shapers of the Systems Engineering discipline by his important academic, scientific and consulting contributions for advancing the scientific knowledge and the practice of Systems Engineering from 1960s in the topics of: Systems Integration and Architecting, Complex Adaptive Systems and Knowledge Management, Economic Systems Analysis, and Systems Management. Professor Sage is author or co-author from several books on Systems Engineering and of more than 100 papers in top journals and conferences. Professor Sage has been Editor in Chief of the IEEE Transactions on Systems, Man, and Cybernetics (January 1972 - December 1998), Editor of Automatica (July 1981 - June 1996) and Co-Editor in Chief (with W. B. Rouse) of Information, Knowledge, and Systems Management, IOS Press, from April 1999 at present. Currently, Professor Sage is the Editor In Chief of the International Council on Systems Engineering Journal Systems Engineering from, January 1998. He has received several international awards for his academic and professional activities such as: the International Council on Systems Engineering (INCOSE) Pioneer Award (2002), the Eta Kappa Nu Eminent Member Award (2002) and the Third Millennium Medal IEEE (2000) among others. His formal education is a B.S.E.E. (The Citadel, 1955), a S.M.E.E. (Massachusetts Institute of Technology, 1956), a Ph.D. (Purdue University, 1960), a D.Engr. (University of Waterloo, 1987, Honoris Causa) and a D.Engr. (Dalhousie University, 1997, Honoris Causa). His wisdom has been gained during more than 40 years doing teaching, research and consulting. In IJITSA journal, we are honored to present the system’s view and thoughts from Professor Sage with the goal to contribute in the systemic integration of the Information Systems, Systems Engineering and Software Engineering disciplines. IJITSA’s questions and Professor Sage’s views are presented in next paragraphs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.009 |
| Scholarly communication | 0.007 | 0.011 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.015 | 0.006 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".