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Record W4312245352 · doi:10.1017/9781800104631.015

Afterword: A Personal Tribute

2022· other· en· W4312245352 on OpenAlexaboutno aff
Derek Pearsall

Bibliographic record

Venuenot available
Typeother
Languageen
FieldArts and Humanities
TopicSouth Asian Cinema and Culture
Canadian institutionsnot available
Fundersnot available
KeywordsTributeArtArt history

Abstract

fetched live from OpenAlex

I first met Linne Mooney in 1974 at the University of Toronto, where I had been invited to give a lecture and where she was newly embarked on a Ph.D. She was very young. Later she took up a post at the University of Maine in Orono, and when I left York to go to Harvard in 1985 I began to see more of her when she came down to attend our weekly medieval seminar, and on other occasions. At this time she was preparing an edition of the Kalendarium of John Somer, which was published in 1998 in the Chaucer Library Series. She was also working on some of the most complex and difficult of fifteenth-century literary manuscripts, most of them miscellanies, almost as if she were choosing them because they were difficult and therefore more interesting. She gave a talk at the Harvard seminar on one occasion about the lyrics in the famous miscellany in Cambridge, Trinity College, MS R.3.19, beginning to make proper sense of them for the first time. She was also doing ongoing and never-ending work on the many manuscripts of Lydgate's Verses on the Kings of England , trying to establish some sort of order and coherence to their bewildering variety. Lydgate's Verses is not a work of great literary interest, to say the least, but Linne was not much worried by this, in fact she seemed to revel in it. I had to learn that my own interest in manuscripts, chiefly as valuable repositories of important literary texts, was not everyone’s. I went to a talk a long time ago by one of Linne's eminent predecessors as a codicologist and palaeographer, devoted to a description of a particular MS. I asked her afterwards, in my old-fashioned way, what was the text in the MS? ‘I don't know’, she said, ‘I don't do that sort of thing’. In 1999 I organised a conference at Harvard called ‘New Directions in Medieval Manuscript Studies’, and one of the speakers I invited, keen to give her a larger hearing, was Linne. Her talk was about her work in identifying the hands of fifteenth-century vernacular scribes which appear in more than one manuscript.

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)0.018
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: Other · Consensus signal: none
Teacher disagreement score0.282
Threshold uncertainty score0.944

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.018
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0080.002
Scholarly communication0.0110.008
Open science0.0030.005
Research integrity0.0070.013
Insufficient payload (model declined to judge)0.2820.402

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 head0.014
GPT teacher head0.194
Teacher spread0.180 · 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
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
Published2022
Admission routes1
Has abstractyes

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