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
Discussion forums in Massive Open Online Courses (MOOCs) represent a unique opportunity for insight into the formation of learning communities. Discussions are the locus of a MOOC’s social experience and the forum space a testing ground of instructor presence. In MOOCs, the global scale of peer-to-peer contact represents a network of cross-cultural sharing and collaborative problem-solving, a relationship that generates the opportunity for experts to scaffold a novice’s learning (Anderson, A. (Ed.) (2008). Theory and practice of online learning . Edmonton, AB. Athabasca Press). How learners acquire and build upon prior knowledge sets, sharing them with others in discussion forums, contributes to the robustness of learning communities. As extant literature suggests, collaborative learning accelerates content acquisition, providing a diverse approach to intellectual inquiry based upon the social construction of meaning. This paper outlines a framework for diagnosing a scaffolding of knowledge based on the social and contextual patterning in MOOC discussion forums.
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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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