Learning from experience: a theoretical framework for the work activity analysis and safe design
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
Many studies were conducted in GIPC-PROSPER, a French multi-field project concerning “Integration of Prevention into Design process” (Fadier, Neboit, & Ciccotelli, 2003). One of the main objective consisted in developing a theoretical framework and methodological rules allowing the best to be taken into account into design process the conditions of use equipment work. The main result was the development of new concepts (boundary Activities Tolerated during Use and Boundary Conditions Tolerated by Use). Results showed that the analysis of the work activity could be a real tool for a better design. Thus, the return-of-experience at the end of the analysis of work activities can involve different type of designers and owners. The capacity of these analyses to anticipate future operation is significant, even if the way in which they can be integrated into the design is still lacking. However, the ultimate goal is to integrate them in the specifications that need to be satisfied.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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