3.5.2 Continuous Appraisal Method (CAM)… A New Paradigm for Benchmarking Process Maturity
Bibliographic record
Abstract
ABSTRACT The publication of EIA/IS 731.1 Systems Engineering Capability Model (SECM) establishes a standard against which an organization determines its level of process maturity for systems engineering. EIA/IS 731.2 SECM Appraisal Method provides guidance on the conduct of an appraisal using the SECM. The EIA/IS 731.2 method of derterming the process maturity level is based upon the Software Engineering Institute's (SEI) CMM® (Capability Maturity Model) Based Assessment for Internal Process Improvement (CBA IPI) that has been the engineering process maturity appraisal method of choice since its first use in 1994. This paper presents an alternative method for appraising an orgnaization's engineering maturity level—the Continuous Appraisal Method (CAM). CAM provides a significant advantage over the CBA IPI in three areas. First the cost of using CAM is significantly lower than using CBA IPI. Second, CAM allows considerable felexability in scheduling program time during the appraisal. Third, CAM becomes an integral part an organization's process improvement initiative by providing timely feedback on process improvement opportunities.
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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 | 0.035 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
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".