The Socialist Project on Social Media Platforms: Anticapitalist Organization in Platform Capitalism
Bibliographic record
Abstract
This article is a self-reflexive case study of the Socialist Project's (SP) tactical uses of Meta's Facebook and Google's YouTube platforms. Formed in early 2003 by Leo Panitch (1945–2020), Greg Albo, Sam Gindin, Herman Rosenfeld, and others, the SP is a small Toronto-based democratic socialist organization that for nearly two decades has contributed to wider efforts to build and sustain an anticapitalist “infrastructure of dissent” and “radical imagination.” While Facebook's and YouTube's ownership structures, business models, and datafication and commodification mechanisms limit the SP's tactical uses of these platforms, the SP's agency to use these to try to make history in digital conditions not of its own choosing is significant. This article argues that the SP's tactical use of social media platforms exists between structure and agency, at the interface of top-down platform capitalist business models, mechanisms, and logics and bottom-up anticapitalist organization building, public pedagogy, and alternative media making.
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.
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 | 0.010 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.058 |
| Scholarly communication | 0.012 | 0.011 |
| Open science | 0.001 | 0.016 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".