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Record W4214531914 · doi:10.1515/9781474403900

Nine Centuries of Man

2017· book· en· W4214531914 on OpenAlexaboutno aff
Lynn Abrams, Elizabeth Ewan

Bibliographic record

VenueEdinburgh University Press eBooks · 2017
Typebook
Languageen
FieldArts and Humanities
TopicScottish History and National Identity
Canadian institutionsnot available
Fundersnot available
KeywordsHistoryArt

Abstract

fetched live from OpenAlex

What did it mean to be a man in Scotland over the past nine centuries? Scotland, with its stereotypes of the kilted warrior and the industrial ‘hard man’ has long been characterised in masculine terms, but there has been little historical exploration of what masculinity actually means for men (and women) in a Scottish context. This interdisciplinary collection explores a diverse range of the multiple and changing forms of masculinities from the late eleventh to the late twentieth century, examining the ways in which Scottish society through the ages defined expectations for men and their behaviour. How men reacted to those expectations is examined through sources such as documentary materials, medieval seals, romance, poetry, begging letters, police reports and court records, charity records, oral histories and personal correspondence. Focusing upon the wide range of activities and roles undertaken by men ‒ work, fatherhood and play, violence and war, sex and commerce ‒ the book also illustrates the range of masculinities which affected or were internalised by men. Together, they illustrate some of the ways Scotland’s gender expectations have changed over the centuries and how more generally masculinities have informed the path of Scottish history. Contributors Lynn Abrams, University of Glasgow Katie Barclay, University of Adelaide Angela Bartiem University of Edinburgh Rosalind Carr, University of East London Tanya Cheadle, University of Glasgow Harriet Cornell, University of Edinburgh Sarah Dunnigan, University of Edinburgh Elizabeth Ewan, University of Guelph Alistair Fraser, University of Glasgow Sergi Mainer, University of Edinburgh Jeffrey Meek, University of Glasgow Cynthia J. Neville, Dalhousie University Janay Nugent, University of Lethbridge Tawny Paul, Northumbria University

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)0.003
metaresearch head score (Gemma)0.006
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: Other · Consensus signal: Other
Teacher disagreement score0.029
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0140.018
Scholarly communication0.0080.005
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0170.005

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 head0.039
GPT teacher head0.204
Teacher spread0.165 · 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

Citations2
Published2017
Admission routes1
Has abstractyes

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