Mapping “A Situation of Open Education”: Using Collaborative Relational Mapping to Explore Motivations and Constraint Among Open Educators
Bibliographic record
Abstract
This short paper, analyzes “a situation of open education” using a relational map constructed in collaboration with a group of open educators as part of a larger study of the implications of scale within the field of open education. Applying situational analysis research methodology with its feminist and post-structural underpinnings, the purpose of this study is not to seek a “right” or “wrong” approach to scale but instead to invite a small group of open educators to deconstruct the concept of scale. This research approach is qualitative, critical and tentative and is written in the first person in alignment with the belief that research is neither objective nor neutral. The relational map presented offers insight into the desires of open educators to increase access, enact social justice, extend beyond the course and reach wider audiences in ways that consistently reject mass standardization. It also highlights the ways in which their efforts are constrained by overwork, a constraint that compels some open educators to adopt large-scale technologies and approaches. Building the foundation for the next stages in the larger research project, it highlights open educators’ complicated relationships with scale. This paper concludes that there is a need to better differentiate the mechanisms of scale through which transformation with open education might be achieved.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 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".