WITH SPLINTERS (OR STARS) IN OUR EYES: ON READING THE FRANKFURT SCHOOL WITH MARTIN JAY
Bibliographic record
Abstract
ABSTRACT This mostly admiring review article focuses on Martin Jay's 2020 essay collection entitled Splinters in Your Eye: Frankfurt School Provocations. Though it highlights details and insights from nearly every essay in the collection, the review devotes significant attention to chapter 4, which focuses on the relationship of the Frankfurt School's first‐generation scholars with Sigmund Freud. The departure point for my engagement with Jay's fourth chapter is the translation of the German word Trieb (drive) as “instinct” throughout The Standard Edition of the Complete Psychological Works of Sigmund Freud. Although Jay's treatment of Max Horkheimer's, Theodor W. Adorno's, and Herbert Marcuse's recourses to Freudian psychoanalysis emphasizes their abiding commitment to Freud's theory of instinctual forces (over and against objections to his biologism), the question of whether a drive differs from an instinct does not arise. This question therefore offers an occasion to speculate on how distinguishing more firmly between instinct and drive might matter for the Frankfurt School's opposition between first and second nature. Though I praise Jay's decision to include a chapter on Miriam Hansen's Benjaminian revision of the public sphere, I also criticize his practice, in this volume at least, of consigning most scholarship authored by women to the endnotes rather than engaging with it in the main text.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| 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".