“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
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.026 | 0.017 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".