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Record W345375648

Living Beauty: The Art of Liturgy

2011· article· en· W345375648 on OpenAlexaboutno aff
Elaine Belz

Bibliographic record

VenueCithara · 2011
Typearticle
Languageen
FieldArts and Humanities
TopicCatholicism and Religious Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLiturgyBeautyGarciaEucharistPhilosophyArtAestheticsTheologyArt historySociologyHumanities
DOInot available

Abstract

fetched live from OpenAlex

Living Beauty: The Art of Liturgy. By Alejandro Garcia-Rivera and Thomas Scirghi. Lanham, MD /Toronto: Rowman & Littlefield Publishers, 2008. Pp. 201 . $21.95. Living Beauty was co-written by Alejandro Garcia-Rivera and Thomas Scirghi while both were professors at Jesuit School of Theology at Berkeley. The authors alternate writing sections in each chapter, but in very close dialogue. Although I have never met Fr. Scirghi, I was privileged to study briefly under Professor Garcia-Rivera, and, in my experience, such collaboration was typical of him. Many of his classes were team-taught, often bringing interdisciplinary approaches together. For anyone familiar with Garcia-Rivera's work, it is easy to see themes from his classes and prior publications coalesce in Living Beauty, which also points toward his theological cosmology developed in The Garden of God. Liturgical aesthetics, he proposes in introduction, is an approach to understanding and practice of liturgy that cultivates liturgical way of life (6); hence, living Chapter 1 begins to nuance what authors mean by beauty. Scirghi, who writes first in each chapter, makes useful distinction between messy and sloppy liturgy. Messinese, which is inherent in human endeavor, is different from sloppiness that betrays lack of preparation or care. He contrasts messinese with strict adherence to rubrics. Concern for ritual purity has historically led to abuses such as withholding cup from laity; it also reduces mystery of Eucharist to an equation in which real presence of Christ in Eucharist follows necessarily from performing rite correctly. Its goal is efficiency - feeding as many people as possible as quickly as possible - rather than encounter. Garcia-Rivera in turn calls for ressourcement of Often in class he would distinguish between attempt to explain mystery and more appropriate work of rendering it intelligible - developing language to speak about Here he argues that while we may not be able to fully understand it, we do experience Aesthetically speaking, liturgy sharpens our abilities to perceive a sensible mystery. The second and third chapters focus on what Vatican II document Sacrosanctum Concilium identifies as two aims of liturgy: sanctifyinghumanity and glorifying God. These two aims are inextricably related. In chapter two, Scirghi addresses human response of gratitude for God's gifts by asking: What does find beautiful? When ancient Israelites built tabernacle (Exodus 25-40), their artistry was both gift of human freedom (in contrast to their craftsmanship under compulsion in Egypt) and seeing together with God (67) as they followed God's instructions. Further, Scirghi maintains that the worthiness of gift is recognized by its mark of redemption (66), as seen in Gospel story of woman who anointed Jesus' feet. Beautiful liturgy is relational: it provides setting for encounter with God. Garcia-Rivera suggests that praise should be understood not merely as response to 's graciousness, but as mystery proper to humanity. He compares this to bird song, citing scientific research which suggests that birds sing not merely to communicate, but because they enjoy it (75-78). The same is true of Church song. Connecting beauty and holiness, it creates in us habitus of holiness. …

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.006
Scholarly communication0.0050.006
Open science0.0010.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0240.005

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 head0.055
GPT teacher head0.196
Teacher spread0.141 · 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
Published2011
Admission routes1
Has abstractyes

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