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Record W4396693239 · doi:10.11647/obp.0371.09

9. The Eucharist in its Liturgical Context

2024· book-chapter· en· W4396693239 on OpenAlexaff
Luke Clossey

Bibliographic record

VenueOpen Book Publishers · 2024
Typebook-chapter
Languageen
FieldArts and Humanities
TopicChristian Theology and Mission
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsEucharistContext (archaeology)PhilosophyTheologyHistoryArchaeology

Abstract

fetched live from OpenAlex

This chapter explains the logistics of the liturgical calendar and the eucharistic ritual. On the production side, the number of masses performed was not chosen for its resonance, but was maximized based on worldly constraints—the availability of space (the number of altars), money, and time. Similarly, on the consumption side, enthusiasts running between churches sought to behold the highest possible number of masses, a number without any deep-ken meaning. In the deep ken, the glory of the mass was optimized by carefully orchestrating time, place, and other circumstances so they would consonate with each other. In contrast, the interest in maximizing the number of heard masses depended more on the plain ken. Especially in Bohemia and England, but even as far away as Tunisia, critics expressed pointed doubts that the eucharist ritual could turn wine and bread into Jesus's body and blood. Often these objections assumed a plain ken regarding space, which created obstacles to the transformation of matter, to the perception of the invisible, and to the possibility that Jesus could exist simultaneously across the breadth of Christendom. Other critics fought over interpretations of the Jesus's words used to institute the mass. The intensity of these debates fuelled rumours of desecrations. A number of miracles demonstrated that the consecrated host was powerful, indestructible, and unable to be misplaced. Local and transregional cults developed around hosts that bled to empirically drown out all these intellectual controversies.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.443
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0050.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0440.003

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 head0.043
GPT teacher head0.254
Teacher spread0.211 · 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; both teacher heads agree on what is shown here.

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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