Mobile Knowledge, Karma Points and Digital Peers: The Tacit Epistemology and Linguistic Representation of MOOCs / Savoir mobile, points de karma et pairs numériques : l’épistémologie tacite et la représentation linguistique des MOOC
Bibliographic record
Abstract
Media representations of massive open online courses (MOOCs) such as those offered by Coursera, edX and Udacity reflect tension and ambiguity in their bold promise of democratized education and global knowledge sharing. An approach to MOOCs that emphasizes the tacit epistemology of such representations suggests a richer account of the ambiguities of MOOCs, the unsettled linguistic and visual representations that reflect the strange lifeworld of global online courses and the pressing need for promising innovation that seeks to serve the restless global desire for knowledge. This perspective piece critically appraises the linguistic laboratory of thought such representation reveals and its destabilized rhetoric of technology and educational practice. The mobile knowledge of MOOCs, detached from context and educational purpose and indifferent to cultural boundary distortions, contains both the promise of democratized education and the shadow of post-colonial knowledge export. Les représentations médiatiques des cours en ligne ouverts et massifs (MOOC en anglais) comme ceux offerts par Coursera, edX et Udacity reflètent une tension et une ambiguïté occasionnées par leur audacieuse promesse de démocratisation de l’éducation et de partage global du savoir. Étudier les MOOC en accentuant l'épistémologie tacite de ces représentations mène à une explication plus riche des ambiguïtés inhérentes aux MOOC, de l’incertitude des représentations linguistiques et visuelles reflétant l’étrange monde vécu des cours en ligne à l’échelle globale et le besoin pressant d'innovation prometteuse visant à répondre au désir insatiable de connaissance à travers le monde. Le présent essai évalue de manière critique le laboratoire linguistique d’idées révélées par une telle représentation ainsi que son discours instable sur la technologie et sur les pratiques pédagogiques. Libéré de tout contexte et d’objectif pédagogique et indifférent aux distorsions des barrières culturelles, le savoir mobile des MOOC contient à la fois la promesse d'une éducation démocratisée et le spectre d’un savoir postcolonial.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".