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Record W2961289320 · doi:10.32396/usurj.v5i2.366

The Desert in Words

2019· article· en· W2961289320 on OpenAlexaffvenue
Jackson Davis Hase

Bibliographic record

VenueUSURJ University of Saskatchewan Undergraduate Research Journal · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Linguistic Studies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsAsceticismDesert (philosophy)Presentation (obstetrics)Rendering (computer graphics)Power (physics)HistoryLiteratureLinguisticsPsychologyPhilosophyEpistemologyComputer scienceArtArtificial intelligenceArchaeology

Abstract

fetched live from OpenAlex

This paper textually investigates the alphabetical Apophthegmata Patrum, a text written in the late 5th or early 6th century CE that claims to record the sayings of the Egyptian Desert Fathers. The purpose of this investigation is to better understand the nature of Christian ascetic authority at this time as it moved from an oral to a written tradition. As this text bases its presentation of authority on sayings, or ‘words’, this paper will begin by focusing on a corpus of sayings which reveal how this text understands the power of ‘words.’ This text understands itself as enacting authority via words with the intention of transforming its readers. Once this paper has demonstrated this understanding, it will continue to outline a new understanding of the text’s contradictions: that ‘words’ must be prescribed based on an individual and their situation, thus rendering contradictions non-problematic. Therefore, self-analysis and self-prescription of ‘words’ became necessary to ascetics as ‘words’ became written and not performed by the Fathers themselves. This aspect of written ascetic authority also exists within the later systematic Apophthegmata Patrum and other ascetic writings, with differences occurring because of their perceived audiences.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.319
Teacher spread0.276 · 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 teacher head, not a consensus.

Study designQualitative
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
Published2019
Admission routes2
Has abstractyes

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