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Record W7114835153

Medieval Slavic Summer Institute at Ohio State: Celebrating a Quarter Century of a Unique Educational Experience

2025· other· en· W7114835153 on OpenAlexaboutno aff

Bibliographic record

VenueThe Knowledge Bank (The Ohio State University) · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsSlavic languagesQuarter (Canadian coin)Reading (process)ScholarshipState (computer science)
DOInot available

Abstract

fetched live from OpenAlex

The first MSSI in 1999 was 3 weeks long, subsequent institutes have lasted 4 weeks. The most recent MSSI 2024 was the 12th biennial institute. There have been 133 full-time, in-person participants mostly from North American & European universities; the top 10 institutions represented are: Ohio State (40 participants), Univ. of Michigan (9), Universidad Complutense de Madrid (8), Univ. of Cambridge (6), Univ. of Toronto (5), Univ. of Chicago (4), Univ. of Kansas (3) & UCLA (3), Central European Univ. (2) & Harvard (2). In 2024, Atmoja Bose became the first participant from the Univ. of Delhi (India), and Aleksa Karajić (Univ. of Belgrade, Serbia) the first from a Slavic country. We had previously focused on instructing students who did not have access to experts and manuscripts in Slavic Cyrillic at their home universities such as in Serbia, Bulgaria, North Macedonia, and Russia. Predrag Matejic taught MSSI 1999-2017, Daniel E. Collins – MSSI 1999-2019; M.A. Johnson took over from Predrag in 2019, and Bojan Belić (MSSI 1999) has taught Church Slavonic since MSSI 2022. From the beginning there have been guest lecturers, including the Very Rev. Dr. Mateja Matejic in 2003. Professor Jenn Spock’s practicum in reading Muscovite cursive has been a staple since 2006, and Professor Eric J. Johnson’s Western manuscript codicology and printing since 2011. Whenever possible, MSSI alumni are hired as RCMSS graduate research associates; since 2015, MSSI alumni have been invited back as MSSI guest lecturers.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.190
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.003

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 head0.015
GPT teacher head0.253
Teacher spread0.238 · 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
Published2025
Admission routes1
Has abstractyes

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