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Appropriate Combatants

2018· book-chapter· en· W2915055621 on OpenAlexaboutno aff
Gina M. Martino

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMilitarizationBureaucracyPolitical scienceColonialismMilitarismCompensation (psychology)CriminologyEconomic historyHistoryPolitical economyPublic administrationLawSociologyPoliticsPsychology

Abstract

fetched live from OpenAlex

This chapter marks the beginning of the book’s study of the second phase of these conflicts. Beginning around 1700, Britain and France became increasingly involved in their colonies’ affairs. This growing imperial control resulted in the increased militarization of New England and New France, as regular troops joined provincial forces with greater frequency. These imperial military societies also depended more on highly fortified structures to defend their colonial territory. The chapter examines how these changes influenced women’s participation in war and how colonists and imperial officials perceived women’s war making. In New England, women received land grants and compensation as veterans even as changes in ideas about women’s gender roles as private, rather than public, actors in separate spheres resulted in colonists describing women as inhabitants of an emerging homefront. At the same time, officials in New France worried about the potential for treasonous activities between Canadian women and French soldiers involved in sex scandals in the crowded fortified towns along the coast. Despite these fears, Canadian women continued to serve in the colony’s growing military bureaucracy, financing fortifications and supporting the war effort through commerce.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.690
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.025
GPT teacher head0.197
Teacher spread0.172 · 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 teacher head, not a consensus.

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
Published2018
Admission routes1
Has abstractyes

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