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Record W2796349460 · doi:10.1093/notesj/gjy020

Spiritual Alchemy in Andrew Marvell’s Eyes and Tears

2018· article· en· W2796349460 on OpenAlexaff
Gary Kuchar

Bibliographic record

VenueNotes and Queries · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsStanzaAlchemyDepictionPoetryLiteratureSAINTTheme (computing)ArtPhilosophyArt history

Abstract

fetched live from OpenAlex

THE question still remains unsettled of whether Andrew Marvell’s Eyes and Tears is a religious poem in which he reworks the poetry of tears tradition associated with Robert Southwell, or a secular poem that is primarily responsive to non-religious depictions of female weeping. Since stanza VIII refers to Mary Magdalene those who see the lyric as consistently religious in orientation view it as essentially unified, while those who read the poem as largely secular discern a degree of discontinuity at work in it.1 The distance between these positions might be bridged somewhat by considering how stanza VI shows Marvell responding to Southwell’s depiction of spiritual alchemy in Saint Peters Complaynt, a theme that is developed in the poetry of tears tradition through Donne, Crashaw, Herbert, and others. For although the stanza seems strictly focused on natural phenomena, it nevertheless alludes to traditions of spiritual alchemy and thus leads relatively smoothly to the depiction of Mary Magdalene and her redeemer two stanzas later. Furthermore, stanza VI’s references to spiritual alchemy also illuminate some key imagery in the poem including the union of eyes and tears that closes the lyric.

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)0.003
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: Empirical · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.014
Scholarly communication0.0070.003
Open science0.0000.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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
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

Citations1
Published2018
Admission routes1
Has abstractyes

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