‘How are we going to be able to reach a higher degree of self-determination?’: A conversation with writer Max Czollek about ‘Radical Diversity’
Bibliographic record
Abstract
Max Czollek just published a translation of his book De-Integrate!: A Jewish Survival Guide for the 21st Century (translated by Jon Cho-Polizzi at New York Restless Books, 2023), a controversial, often humorous and best-selling polemic first published in Germany at Hanser Verlag, Munich, in 2018 under the title Desintegriert Euch. De-Integrate! is a battle cry against Jewish assimilation into a dominant culture that seeks to paint over the past – and a handbook for minorities on how to embrace their differences and resist rising nationalism, anti-Semitism, xenophobia and racism. Max Czollek was very generous by inviting me to his apartment in Berlin-Kreuzberg in the summer of 2022, where we publicly talked about narratives of non-belonging and belonging, migration and postmigration, as well as diversity and memory politics. This article is a shortened and edited version of our conversation in anticipation of his new publication De-Integrate!
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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 | 0.013 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.043 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.009 | 0.020 |
| 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".