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Record W4388915598 · doi:10.15382/sturii2023114.26-34

The issue of belonging of metropolitan Joasaph (Skripitsyn) to the circle of “non-possessors”

2023· article· en· W4388915598 on OpenAlexaboutno aff
Vladislav Petrushko

Bibliographic record

VenueSt Tikhons University Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsMonasticismMetropolitan areaQuarter (Canadian coin)HistoriographyContext (archaeology)HistoryPolitical scienceLawAncient historyArchaeology

Abstract

fetched live from OpenAlex

The article contains a critical analysis of the opinion prevailing in russian historiography that the metropolitan of All Russia Joasaph (Skripitsyn), unlike his predecessor Daniil, was a supporter of the so-called «non-possessors» - representatives of russian monasticism who called for renouncement of monasteries from land estates. Based on the sources cited in the article, the author comes to the conclusion that the opinion that metropolitan Joasaph (Skripitsyn) belongs to the «non-possessors» should be recognized as unfounded. It seems that in the context of modern ideas about the controversy between "Josephites" and "non-possessors" it would be generally incorrect to raise the question of the "non-possessiveness" of Ioasaph (Skripitsyn). Russian monasticism in the second quarter of the 16th century. was not totally divided on the issue of attitude to the monastic lands into two irreconcilable camps. The presence in his midst of groups of "Josephites" and "nonpossessors" who occupied extreme positions on the issue of church land ownership does not mean that all the rest certainly had to decide on such a "party" affiliation. Joasaph (Skripitsyn), unlike Metropolitan Daniel and Vassian (Patrikeev), most likely was alien to such a biased view of both the problem of monastic lands and monasticism in general.

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)0.002
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: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0130.014
Scholarly communication0.0050.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.020
GPT teacher head0.304
Teacher spread0.285 · 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
Published2023
Admission routes1
Has abstractyes

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