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Record W3087836325 · doi:10.33137/q.i..v38i1.31164

Fables and Faith: <i>Favoleggiare</i> in the <i>Commedia</i>

2018· article· en· W3087836325 on OpenAlexvenueno aff
Mary-Michelle DeCoste

Bibliographic record

VenueQuaderni d italianistica · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicRenaissance and Early Modern Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPilgrimFaithTragedy (event)VerbHeavenTheologyOrder (exchange)LiteraturePhilosophyYesterdayHistoryArtLinguistics

Abstract

fetched live from OpenAlex

The verb favoleggiare appears twice in Dante’s Divina commedia, both times in the Paradiso. An examination of the use of this word, alongside a secondary consideration of the word favola as it is used elsewhere in the Paradiso, suggests the poet’s concern with the relationship between knowledge, particularly the shared beliefs of a community, and faith. As the pilgrim progresses on his journey through heaven, he comes to learn that the epistemology perpetuated through fables, while it may have its uses, is not enough to allow him to regain the diritta via Firmly rooted in the past, fables cannot adequately explain the sense behind human tragedy, nor do they provide all the tools necessary to acquire salvation. As the pilgrim will come to learn, we must look away from our human community to the divine, which remains unchanged and unaffected by the course of human affairs. It is this that the pilgrim must bear in mind through the suffering that awaits him on earth as he keeps his eyes on his heavenly reward. In order to do this, he must abandon his reliance on fables and accept that the cross is the only framework upon which a holy life can be based.

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: Empirical · Consensus signal: none
Teacher disagreement score0.016
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0040.003
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.002

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 head0.038
GPT teacher head0.250
Teacher spread0.213 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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