The problem of the web: Can we prioritize both participatory practices and privacy?
Bibliographic record
Abstract
This paper is a critical case study tracing the professional history of a self-professed open educator over more than two decades. It frames the narrative of an individual as a window on the broader arc of the field, from early open learning as a means of widening participation, through the rise of the participatory web at scale, to the current datafied and extractive infrastructure of higher education. It outlines how the field of online education has changed, as the web and the social and societal forces shaping use of the web have shifted. Through these lenses of change, the case study explores the dilemma facing open and participatory education at this juncture: that the current structure of the web threatens privacy, higher education governance structures, and the spirit of open, participatory sharing. The paper explores the problem of the web as one without direct solutions but does consider ways that educators might mitigate their open practice in more critical directions.
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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 | 0.064 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.025 | 0.127 |
| Scholarly communication | 0.037 | 0.084 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.014 | 0.016 |
| Insufficient payload (model declined to judge) | 0.007 | 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 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".