MétaCan
Menu
Back to cohort
Record W4399180933 · doi:10.1515/9780228021568

Ghost Stories

2024· book· en· W4399180933 on OpenAlexaboutno aff
Judith Adamson

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2024
Typebook
Languageen
FieldSocial Sciences
TopicGothic Literature and Media Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsArt

Abstract

fetched live from OpenAlex

A biographer is, in a sense, the ghostwriter of someone else’s life, trying to keep out of the way but inevitably leaving an imprint and being changed in the enterprise. In her memoir Judith Adamson, a professional biographer, tells the ghost’s side of the story. Adamson reveals the questions she asked herself as she researched and wrote, as well as the personal challenges she faced in producing a lively sense of the figure she was recreating on the page, drawing an unbreakable connection between the personal and the professional. Crossing paths with literary luminaries of the twentieth century, she went on to collaborate with Graham Greene on Reflections , the last of his books published in his lifetime. She recounts how she was entrusted with the publication of Leonard Woolf and Trekkie Ritchie’s love letters; how she found a way to hunt down Charlotte Haldane, one of the first women on Fleet Street; and how she came to write the biography of Max Reinhardt, the man behind the finest English publishing house of the mid-twentieth century. A sharply observant and self-effacing narrator, Adamson brings vividly to life an anglophone upbringing in mid-century Montreal, the London literary scene, and the struggles faced by the women intellectuals of her time. Ghost Stories is a tale of good luck and the hard sleuthing of biographical work before the digital age.

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)0.016
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: Other
Teacher disagreement score0.211
Threshold uncertainty score0.707

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0070.003
Scholarly communication0.0120.010
Open science0.0020.012
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.2110.071

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 head0.239
Teacher spread0.225 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueMcGill-Queen's University Press eBooksSame topicGothic Literature and Media AnalysisFrench-language works237,207