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Record W4404801245 · doi:10.1017/9781009423120.003

Psalm Charms as Aids against Illness

2024· book-chapter· en· W4404801245 on OpenAlexaff

Bibliographic record

VenueCambridge University Press eBooks · 2024
Typebook-chapter
Languageen
FieldArts and Humanities
TopicBiblical Studies and Interpretation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineHistoryPsychology

Abstract

fetched live from OpenAlex

The praying of psalms is the subject of Chapter 2. Psalms are frequently sung in charm rituals. They are carefully prescribed to help heal human and animal illness. Acute and painful diseases, such as diarrhea and carbuncles, are treated with psalms, as is fever. Even madness and “fiend-sickness” might respond to them, it was hoped. Psalms have great resonance for the English. They lie at the core of medieval liturgies, both monastic and public. They give hope to the suffering during the Visitation of the Sick. They were offered more generally as personal prayers and as penance. Chapter two establishes the petitionary nature of the psalms used in charm remedies. It demonstrates how psalms structure and organize charm performance with regard to other incantations. Psalms serve as practical prayers, the functionality of which arises out of each psalm’s generic form. They seek God’s assistance by asking the Lord directly or indirectly for aid. Psalms that use figurative language relevant to a charm’s objective employ metaphor and simile that act as vehicles for sympathetic magic. Charms render psalm incantations as powerful medicine for those in need.

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)0.001
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 score0.011
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0030.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.002

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 head0.026
GPT teacher head0.202
Teacher spread0.176 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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