Decolonizing the Irish: The International Resistance and Entrenchment of the Global Irish Diaspora
Bibliographic record
Abstract
Narratives of Irish decolonization often take up local (rather than global) arguments focused on the liberation of Ireland, instead of looking to the participation of Irish people in decolonization efforts internationally. This paper argues that the Irish diaspora, whose population has extended into all corners of the Earth, has a key role to play in decolonization not simply because of the history of anti-colonialism in Ireland and its role as a test site for British colonialism, but specifically because of the need to extend sentiments about national liberation to the nations whose oppression the diaspora has become entrenched in. Through examining on historical examples of Irish roles in the colonization of Canada, the United States, and Australia, this paper explores some of the ways that the desire to contribute to the liberation of Ireland within the Irish diaspora has often become linked to participation in colonization. In so doing, it argues that the Irish nation cannot become decolonized by liberating its own land alone; it must become a force for anti-colonialism by rejecting participation in colonial occupation wherever the Irish find themselves. Drawing attention to opportunities for advancing allieships between the diaspora and other nations struggling against colonialism, the author puts forth a call to action for decolonizing the Irish.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.029 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".