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Deploying Amazons

2018· book-chapter· en· W2912487507 on OpenAlexaboutno aff
Gina M. Martino

Bibliographic record

VenueUniversity of North Carolina Press eBooks · 2018
Typebook-chapter
Languageen
FieldSocial Sciences
TopicAmerican Constitutional Law and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsHistoryColonialismAmazon rainforestGender studiesPolitical scienceSociologyLawArchaeology

Abstract

fetched live from OpenAlex

Chapter 3 explores the relationship between women’s war making in the northeastern borderlands and propaganda. It argues that political and religious leaders used accounts of women’s martial activities to improve morale and influence policy at local, colonial, and imperial levels. Images of Amazons and other mythical and historical women warriors often appeared in this propaganda, establishing a precedent for women’s actions in North America and adding excitement and familiar literary figures that resonated with readers. In New France, Jesuit missionaries used the figure of the Amazon to positively portray Native female combatants as well as brave nuns who traveled to Canada. They also used their published reports, the <italic>Jesuit Relations</italic>, to urge wealthy French women to be brave like Canada’s Amazon-nuns and donate to the mission. In New England, officials held up women who made war (such as Hannah Dustan) as positive, Christian role models when morale was low, and writers such as the Rev. Cotton Mather sent accounts of women’s war making to England in attempts to shape imperial policy.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.993
Threshold uncertainty score0.999

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 studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.242
Teacher spread0.204 · 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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