Issues in societal optimal engineering decision making
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
Optimal decision making in the context of engineering is addressed from the perspective of society, with the aim of optimal decision making being understood as to provide an informed basis for the identification of sustainable societal developments. The paper begins with a discussion of the issues that are presently of main concern in engineering decision making from a societal perspective. Following this, a suggestion is outlined for the hierarchical representation of the typical societal organizational instruments for ensuring such optimal decision making. This representation defines the boundary conditions for the optimization of engineering decision making. Thereafter, based on Bayesian decision theory, the main constituents of decision making are highlighted, and the various problems in the representation and treatment of these in the context of decision making are discussed in light of the most recent developments of research in these areas. This includes the representation of society in decision making, decision making subject to uncertainty and lack of knowledge, treatment of risk perception, reconciliation of expert opinions, consistent risk assessment, and aspects of socio-economically sustainability.
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.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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