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Record W4392151098 · doi:10.34019/2448-2137.2022.39964

How many messiahs, how many alephs? Levinas’ talmudic “messianic texts” in three numbers, and André Neher’s biblical response

2023· article· en· W4392151098 on OpenAlexaff
Bettina Bergo

Bibliographic record

VenueRevista Ética e Filosofia Política · 2023
Typearticle
Languageen
FieldArts and Humanities
TopicPhilosophy, Ethics, and Existentialism
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsPhilosophyLiteratureEpistemologyArt

Abstract

fetched live from OpenAlex

This article approaches Levinas’s 1963 Talmudic reading entitled “Messianic Texts” in light of the metaphoric numbers 0, 1, and 2. “Zero” will refer to unforeseen silences in the Talmudic text in question (here, Rabbi Eleazar’s sudden silence in the debate about the conditions of redemption, as well as commentator Rashi’s silence on Talmudic discussions about a certain “identity” of the messiah. The number “one” concerns a textual hapax: Rabbi Hillel’s historicist dismissal of the messiah as promise and open future—a position virtually anathema to rabbinics (inter alia) but nevertheless preserved by the Talmud. My metaphoric numbers strategy turns, finally, to the curious presence of “allegorical doubles” in the Bible, which Levinas describes as a configuration of textual “eidetics.” Using my three numbers (0, 1, 2) as an elementary analytic grid, I turn from Levinas’ “Messianic Texts” to André Neher’s biblical commentary on Levinas’s presentation—a commentary similarly concerning messianism but no longer in the Talmud. My purpose is dual: to sketch the context of this complex Talmudic reading, to offer one (idiosyncratic) reading-strategy focusing on two events of “silence,” the future anterior of the “messiah” who will have been but will come no more, and finally the play of identity-in-difference in the biblical doubles.
 
 Keywords: “Messianic Texts,” Vladimir Jankélévitch, André Neher, messianisms, world-to-come, the Samozvanetz.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.868
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.057
GPT teacher head0.286
Teacher spread0.229 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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