Using cognitive work analysis to compare complex system domains
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
There are several reasons to compare and transfer knowledge between complex socio-technical systems. For example, there have been attempts to transfer lessons and knowledge from aviation to health care. Conceptually, understanding system differences in complex environments can highlight the behaviours, processes, values and training that drive performance and ensure safety. Though various approaches exist, we show that an ecological framework, such as cognitive work analysis (CWA), provides an ideal opportunity for the rich comparison of complex systems. This approach is novel, as previous studies have rarely analysed cognitive work analysis models from multiple domains or drawn comparisons. Through a case study, we demonstrate the comparison of work domain analyses and control task analyses from two similar but different health care domains. Through a detailed description of our comparison in a health care setting, we demonstrate that unique and useful insights can be extracted through this process. Though this approach is prefatory, it merits further refinement and use and presents a new way to consume CWA models that currently exist in the literature.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it