Why I am Such a Good Christian: Comments on Gil Anidjar, Blood: A Critique of Christianity
Bibliographic record
Abstract
Abstract Gil Anidjar begins his immensely ambitious bookBloodwith a strange statement/question “Why I am Such a Good Christian.” I begin by examining this question for its implications for cultural hybridity, for myself as well as for Anidjar, through the lens of Anidjar’s concluding discussion of Freud’sMoses and Monotheism. On the way I critically explore Anidjar’s insistence that blood is not a signifier of kinship or ancestry in the Hebrew Bible or in Judaism, and argue that both are in fact much more complex. I suggest also that Christianity has other elements than blood, such as the bread of the Eucharist, and that Anidjar devotes little attention to the differences between Protestant and Catholic Christianity. I conclude by reverting to Freud’s account of an experience of innocence inThe Interpretation of Dreams, as indicative of Freud’s ambivalent position between Judaism and Christianity.
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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 | 0.012 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.038 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.013 | 0.022 |
| 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".