A reflection on Sari Hanafi's ‘societal polarization, academic freedom, and the promise of dialogical sociology’
Bibliographic record
Abstract
In a recent contribution to Dialogues in Sociology , Sari Hanafi (2025) warns about the perils of the ‘cancel culture' in particular, and the gradual weakening of tolerance and open dialogue in the university spaces. He argues that this is mostly the product of the actions of those who considers themselves attached to liberalism, but only symbolically so. In this reflection piece, I share the same concern with Hanafi, and argue that this dangerous development would deprive the western academia from one of its most remarkable strength – that is, its free intellectual environment that allows for critical voices to be heard and flourish. I also argue that this is the product of a profound change in what I have called – following Marx's notion of the ‘organic composition of capital' – the ‘organic composition of activism'. Taking into account two dimensions of activism – virtual vs. on-the-ground nature of activism, and inside vs. outside locus of it – I have offered a 2X2 matrix with four possible combinations; and have argued that most of the activism we are witnessing in the world today, including that of the cultural left or the symbolic liberals is of the virtual/outside-the-locus nature, which represents the lowest level of engagement with reality and the lowest level of effectiveness. I have ended with inviting the left to think more seriously and critically about the ‘cancel culture', in order to break the monopoly that the right has recently gained in defending – unauthentically – the ‘freedom of speech’.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.042 |
| Scholarly communication | 0.014 | 0.020 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.016 | 0.033 |
| Insufficient payload (model declined to judge) | 0.004 | 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".