The Revolution on Facebook: Political Education on Social Media through Nonformal Andragogical Communities of Practice
Bibliographic record
Abstract
This paper considers political education through nonformal communities of practice on social media. While formal and informal classroom environments remain important in the 21 st century, most adult learning occurs in the nonformal context. Communities of practice on social media provide substantial knowledge dissemination and identity-defining communities of practice, also furnishing the opportunity for praxis. Communist Facebook groups provide communities of practice through knowledge dissemination, community membership, and praxis. This paper defines who these groups are, what they do, how they differ from other groups, their education and tools, how they exist outside of state control, and how they fit inside theoretical frames of communities of practice, specifically Hoadley’s (2005) C4P framework, presenting the theory of digital andragogical nonformal educational communities of practice. This paper concludes that in order to understand 21 st century education, nonformal communities of practice on social media require further investigation.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 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".