System-Theoretic Process Analysis (STPA): An Innovative Top-Down Hazard Assessment Method for Based on the System-Theoretic Accident Model and Processes (STAMP) - A Bibliometric Review
Bibliographic record
Abstract
This paper seeks to conduct a comprehensive review of the entire collection of documents published on the development and utilization of STAMP/STPA over the past decade. To achieve this, we have followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology, which serves as a recognized standard for systematic literature reviews in data collection. The study involved nineteen papers devoted to this subject matter, systematically retrieved from the online database Scopus. The findings indicated the need to integrate STAMP/STPA with other systemic safety assessment approaches to create a comprehensive Integrated Decision-Making Framework for Industrial Asset Management. This framework would be instrumental in assessing and managing emerging technology risks, as well as addressing extreme, rare, and disruptive events. Further research would validate its efficiency and practicality. Therefore, future research initiatives will be devoted to conducting case studies in order to obtain more accurate data.
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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 | 0.067 | 0.210 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.011 |
| Bibliometrics | 0.118 | 0.109 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".