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Record W4405005325 · doi:10.1163/2208522x-bja10064

Patriotic Humanitarianism: Toward an Emotional and Experiential History of Children’s Actions During the First World War

2024· article· en· W4405005325 on OpenAlexaboutno aff
Stephanie Olsen

Bibliographic record

VenueEmotions History Culture Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicWorld Wars: History, Literature, and Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMilitarismEmpireAction (physics)Gender studiesSociologyPolitical scienceMedia studiesHistoryLawPolitics

Abstract

fetched live from OpenAlex

Abstract Children throughout the British Empire were encouraged by schools, organisations and communities to participate in the First World War as future citizens and humanitarians. Their emotions, and their experiences, were cultivated collectively. This broad understanding of humanitarianism was sometimes tied to peace activism, but was more often tied to militarism for the majority of children in the British Empire. Children raised money by holding events and selling handmade things. They visited soldiers in hospital and brought them presents. They collected for the Red Cross, the Belgian and Serbian Relief funds and other causes. In Star City, Saskatchewan, and Mitta Mitta, Victoria, and in villages, towns and cities in between, children wrote essays, drew pictures, and composed letters to officials detailing their thoughts and efforts. Children, through their numerous everyday humanitarian actions (often non- material and leaving no trace), contributed to the enormous emotional effort of the war. This essay examines these child-directed humanitarian efforts. Why were so many children motivated to contribute in such substantial ways to the war effort? What sort of emotional and experience formation was required in order to stir children to action? And from where was the impetus – social, school, community, family, peer and/or individual?

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.507
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 studies0.0020.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.255
Teacher spread0.234 · 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
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

Citations1
Published2024
Admission routes1
Has abstractyes

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