Modeling complex socio‐technical systems using the FRAM: A literature review
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.
Bibliographic record
Abstract
Abstract This is a review paper of studies that have employed the functional resonance analysis method (FRAM). FRAM is a relatively new systemic method for modeling and analyzing complex socio‐technical systems. This review aims to address the following research questions: (a) Why is FRAM used? (b) To what domains has FRAM been applied? (c) What are the appropriate data collection approaches in practice? (d) What are the deficiencies of FRAM? A review of 52 FRAM‐related studies published between 2010 and 2020 revealed that FRAM‐based models can be used as a basis for improving safety management, accident/incident investigation, hazard identification/risk management, and complexity management in complex socio‐technical systems. The outcomes also showed that healthcare was the most common domain that employed FRAM (31% of the investigated studies). The results of exploring data collection methods indicated a mixed method (interview, focus group, observation) was employed in 52% of the analyzed studies, and the accident investigation report was the most popular approach in aviation‐related studies. An investigation of the deficiencies of the FRAM showed that it should be upgraded by exploiting supplementary methods to enhance its analytical and computational capacity to help risk analysts and safety managers in complex socio‐technical systems.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it