Strengthening next generation risk decision-making: A contemporary review
Bibliographic record
Abstract
Risk decision-making inherently requires consideration of fundamental principles and other factors pertinent for addressing important health and environmental risks of concern. The risk decision-making process has evolved from linear frameworks to more integrated and dynamic strategies. A recent scoping review mapped this evolution and demonstrated a transition to more holistic and complex approaches. The term next generation risk decision-making captures these contemporary strategies by incorporating all aspects of risk assessment, management, and communication involved in risk decision-making, thereby going beyond recently articulated next generation risk assessment frameworks. While this scoping review included best practices and ten attributes of risk decision-making, it did not address how to consider these factors when developing strategies for next generation risk decision-making. This contemporary review addresses this limitation by discussing the role of decision theories prior to presenting a model for characterizing, categorizing, and visualizing these ten considerations: foresight and planning, research and development, regulatory, risk, upstream and downstream attributes, risk culture, ONE Health lens, broad regulatory factors, risk management, and risk communication. The realist paradigm-based model and corresponding considerations are then analyzed using a strengths, weaknesses, opportunities, and threats analysis of top-down, bottom-up, and fully integrated risk science strategies to next generation risk decision-making.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".