SOCKit: An Online Tool for Systems Thinking
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Systems thinking is an important skillset for understanding dynamic interactions in complex systems. In recent years, there has been a growing recognition that systems thinking is needed in chemistry education to show the interconnection of concepts, to encourage student engagement and to connect learning of chemistry to global sustainability challenges and solutions. Systems mapping, using tools such as Systems-Oriented Concept Map Extensions (SOCMEs), is an important aspect of understanding the systems involved in chemistry, but there are no easy-to-use tools for creating dynamic SOCMEs, especially in educational contexts. At the King’s Centre for Visualization in Science (KCVS.ca), we have created SOCKit (SOCME Online Construction Kit), an interactive learning tool for dynamically creating SOCMEs using force-directed graphs. SOCKit has been designed to be intuitive and mobile-friendly, and can easily create, view, modify, and share SOCMEs to better understand systems and develop a systems thinking toolbox.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".