Immigration after the great famine: A case study of the passengers of the S.S. Canadian
Bibliographic record
Abstract
From 1879 to 1881 Western Ireland suffered a famine that left one million people in a state of destitution. To assist the starving, impoverished farming communities that were scattered across the region English Quaker and philanthropist James Hack Tuke successfully pitched the Tuke Emigration Scheme to the UK government in 1882, lasting through 1884. While historians of Irish immigration have recently begun to research famines other than the Great Famine, very few have delved more deeply into this particular scheme. Of those who have, including Christine Kinnealy and Gerard Moran, analysis has been limited to the perspective of Ireland and thus far only the unpublished research of Margaret Lynch of Cleveland, Ohio’s Irish American Archives Society has delved into the American view of the scheme. While the mission and reports of Tuke and his governmental committee are well documented, investigating the reality of immigrant experiences in the United States requires more effort. Using a database of state and federal biographical records in tandem with Tuke’s sailing manifests, statistical analysis of the status of immigrants can be completed. This research paper along with a complementary ArcGIS Cascade virtual exhibit focuses on one sailing of the Tuke Emigration Scheme, that of the S.S. Canadian in April 1884, uses such analysis to demonstrate that while the scheme was certainly successful in establishing new connections and trends in four particular regions of the United States in later Irish-American immigration as driven by Tuke, in reality it only aligned with Tuke’s more specific vision to a degree. Through a combination of passenger data, the writings of Tuke and his committee, local historical records of Cleveland, Ohio; the Pennsylvania coal mining region; western states; and Holyoke, Massachusetts, and additional source material, the impact and realities of Tuke’s scheme in the United States is revealed.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.004 | 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".