Learning in the Wild: Exploring the Practice of Learning in Open, Online Forums
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Internet provides many opportunities for learning from static resources to conversational spaces for questions, answers, commentary and exploration of topics of interest to participants, whether organized as Q&A sites such as Reddit, hashtag communities on Twitter, or knowledge-sharing sites such as Stack Overflow. Yet, there is limited research on how learning is happening in these spaces. This paper reviews literature and studies about learning in open, online forums to begin to synthesize what is known so far, and to set a research agenda addressing the question: How do people learn in open, online forums? The review builds on work by the author and colleagues, exploring what we refer to as ‘learning in the wild’ (in recognition of Hutchins’ “Cognition in the Wild”, and to reflect the ‘wilds’ of online forums such as Reddit). The increasing use and reach of these sites raises questions not only about what is being learned and what motivates participation in such sites, but also what kind of organization and learning practices are emerging. While it may be thought that such learning, taking place outside the bounds of institutional settings, is informal learning, the research suggests a more complicated picture, dependent on conversation, networks, membership in communities, and community practices, needing to be addressed by drawing on multiple disciplinary perspectives.
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.
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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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 it