Bibliographic record
Abstract
Recent shifts towards spatial issues within education are examined, and mapping is identified as particularly important. The multidisciplinary trend of complexity science is surveyed, in turn, through the lens of physics and education research. The provincial education system of Alberta is considered to be a complex system. Network theory is proposed as a spatial metaphor that effectively describes many complex systems. Amalgamating spatial and complexity thinking from both physics and education, a generalizable network approach is presented to describe and explore the organization of one global aspect of education in Alberta: the courses. By imagining every course as a node, and by linking each course with those that are required as prerequisites, a directed network representing kindergarten through undergraduate studies is constructed in a tailored computing environment, called Calendar Navigator. Important products from such a network description are illustrative visuals, which are intuitively informative. These network graphics and animations can serve as an interactive, dynamic map for students of their local academic surroundings while traveling through the education system, by making clear where they have come from, where they are, and where they can go. A selection of metrics drawn from social network analysis and physics literature, and some here devised especially for course networks, are applied and interpreted. An analytical understanding of the global structure and shape of the education system via network theory can help inform administrators and policy makers to better understand and manage their educational institutions.
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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 | 0.001 |
| 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".