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Erotic Words, Sacred Landscapes, Ideal Bodies: Love and Death in the Song of Songs

2019· other· en· W2995906367 on OpenAlexaff
Francis Landy

Bibliographic record

VenueA Companion to World Literature · 2019
Typeother
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPoetryLiteratureMysticismPatriarchyImmortalityVirtueArtMotif (music)Ideal (ethics)AestheticsPhilosophyHistorySociologyGender studiesTheologyEpistemology

Abstract

fetched live from OpenAlex

Abstract The Song of Songs, composed probably in the third centurybce, is one of the most influential poems in the Western erotic and mystical traditions, by virtue of its appearing in the Bible. It is a dialogue between two lovers in an idyllic pastoral landscape, seemingly without relation to the rest of the sacred text. It is, however, a critique of the biblical tradition, whose implicit question is: what was it all worth? For the Song, the answer is that love alone guarantees an ambiguous immortality. It is thus a tacit counter to Ecclesiastes' refrain that everything is illusory. I discuss the instability of gender in the Song and its questioning of patriarchy, to create a vulnerable maternal space for lovers' intimacy. This space is that of the poetic imagination, which is more real than the everyday world. The metaphors coalescence with the sound patterns of the Song to generate a synthesis of the body, the landscape, history, and the fauna and flora of ancient Israel.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.015
Scholarly communication0.0070.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.015
GPT teacher head0.235
Teacher spread0.220 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations3
Published2019
Admission routes1
Has abstractyes

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