Increasing social connection through a community-of-practice-inspireddesign
Bibliographic record
Abstract
COMMENTARY : CHRISTINE URQUHART Catherine Burns and Adam Euerby used cognitive work analysis to help design a website intended to foster community of practice principles in order to improve networking. First, we need to appreciate the history of cognitive work analysis, and where the ideas about the work domain analysis come from. It's important to recognise that both cognitive work analysis and communities of practice have evidence behind their concepts, and that they are not merely theoretical frameworks that seem to work. Cognitive work analysis comes from studies conducted by Rasmussen and colleagues at the Riso National Laboratory in Denmark in the early 2000s (Naikar, 2017). They were tasked with improving the safety of nuclear power plants in Denmark. Observations confirmed that the hardware was indeed reliable, but that, despite this, accidents could still happen. Human error appeared responsible, when workers were confronted with unfamiliar circumstances. However, the research indicated that had the workers known fully the state of the system, they could have formulated an appropriate response. Later research examined six professional technicians, problem-solving with different types of instruments, which each had a particular fault. Detailed analysis of the verbal protocols (think-aloud protocols) produced a coding scheme that revealed patterns in the reasoning used by the technicians. The technicians reasoned at different levels of abstraction (from the physical properties to the general functional purpose) and at different levels of decomposition (whole system through to a component). This formed what they termed the two-dimensional abstraction-decomposition space. Generally, the technicians started in the most abstract (purpose)/whole system corner and worked through to the opposite corner (physical form/component) – although the line of working could zig zag a little. These findings led to the first stage of cognitive work analysis modelling – the work domain analysis. This was developed by Vicente (2002) (among others) for design of interfaces that displayed three modes of cognitive reasoning: skill-based, rules-based and knowledge-based behaviour. The aim of systems designed through CWA is often to support workers in dealing with unexpected situations. Workers should be able to explore a number of ways of dealing with the situation while remaining within the boundaries of acceptable performance (Naikar, 2017).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.019 | 0.074 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.016 | 0.031 |
| Scholarly communication | 0.010 | 0.019 |
| Open science | 0.006 | 0.011 |
| Research integrity | 0.033 | 0.041 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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 source (direct Gemma or distilled Codex), 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".