MétaCan
Menu
Back to cohort

‘Our Old World Diff’rences are Dead’: The Scottish Migrant Military Tradition in the British Dominions during the First World War

2016· book-chapter· en· W2891768799 on OpenAlexaboutno aff
Stuart Allan, David Forsyth

Bibliographic record

VenueEdinburgh University Press eBooks · 2016
Typebook-chapter
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsFirst world warHistoryWorld War IIAncient historyGenealogyArchaeology

Abstract

fetched live from OpenAlex

Scottish volunteer corps were an established feature of the defence forces of the British Dominions in the decades before the First World War. Displaying and performing the essentials of traditional identity associated with the British army’s Scottish regiments, these military units constituted one form of associational culture for migrant Scots and their descendants. But when, in 1914, the British Dominions joined the imperial war effort, these identities transferred only partially into the expeditionary forces mobilised for overseas service. This chapter considers why it was that, with emigrant Scottish units prominent in the war iconography of Canada and South Africa, the overseas forces of Australia and New Zealand did not similarly embrace the Scottish tradition. The differences are found to lie in administrative arrangements for mobilisation, including conscription, as much as in the relative degrees of Dominion nationalism through which the war was represented and commemorated.

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)0.001
metaresearch head score (Gemma)0.001
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: none
Teacher disagreement score0.113
Threshold uncertainty score0.224

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0060.009
Scholarly communication0.0040.002
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.021
GPT teacher head0.212
Teacher spread0.192 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueEdinburgh University Press eBooksSame topicWorld Wars: History, Literature, and ImpactFrench-language works237,207