Condemned to connection? Network communitarianism in Mark Zuckerberg’s “Facebook Manifesto”
Bibliographic record
Abstract
This article considers Mark Zuckerberg’s 2017 open letter titled “Building Global Community” as a political manifesto. Published just prior to an ongoing series of scandals involving Facebook and the misuse of customer data, the letter outlines Zuckerberg’s plans for the future direction of the company. Using an approach based on Luc Boltanski and Eve Chiapello’s connexionism, combined with Benjamin Bratton’s understanding of platforms and John Bellamy Foster and Robert W. McChesney’s, as well as Shoshana Zuboff’s, analysis of surveillance capitalism, this article argues that the letter remains significant because it constitutes a coherent statement about ubiquitous social media and the future of government in an era characterized by a global turn to authoritarianism. Evoking Japanese philosopher Hiroki Azuma’s reworking of Rousseau’s concept of “General Will” in the social media age, this article warns that one of the most dangerous aspects of the Manifesto is that it might be, in some ways, correct.
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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.029 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".