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Record W4206976728 · doi:10.5406/19364695.41.2.02

“I'm as Good an Irishman as You”: The Ancient Order of Hibernians and the Construction of Irish Ethnicity in Canada and the United States, 1908–1918

2022· article· en· W4206976728 on OpenAlexaboutno aff
Patrick Mannion

Bibliographic record

VenueJournal of American Ethnic History · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsIrishNationalismIrish nationalismFamineEthnic groupHistoryMemorializationGenealogyEthnologyGeographyPolitical scienceGender studiesSociologyArchaeologyLawPolitics

Abstract

fetched live from OpenAlex

Abstract In the early twentieth century, the Ancient Order of Hibernians (AOH) was the foremost Irish ethnic association in North America. At its peak in 1908, there were over 200,000 members spread across thousands of divisions from Cape Breton Island to Hawaii. Across this vast spatial network, the Order cultivated an uncompromisingly Catholic and nationalist conception of Irish historical memory and often led popular engagement with Irish nationalism. Although it was a predominantly Irish American organization, expansion into Canada was an important project for the AOH during this period. This article assesses the transnational networks of Hibernianism from 1908 to 1918, arguing that the Order served as an essential mechanism for the cross-border transfer of Irish culture and identity from the United States into Canada. Initially, there was a strong transnational consensus in the creation of Irish historical memory through the establishment of public sites of famine memorialization. In directing responses to Irish nationalism, however, Hibernian expansion into Canada reveals key differences in how Irish Americans and Irish Canadians understood “being Irish,” particularly as Canadian divisions threatened to secede from the parent organization over its support for Germany in the Great War.

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)0.003
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.655
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.008
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.013
GPT teacher head0.245
Teacher spread0.232 · 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 designQualitative
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
Published2022
Admission routes1
Has abstractyes

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