‘Irish fever’ in Britain during the Great Famine: immigration, disease and the legacy of ‘Black ’47’
Bibliographic record
Abstract
Abstract During the worst year of the Great Irish Famine, ‘Black ’47’, tens of thousands of people fled across the Irish Sea from Ireland to Britain, desperately escaping the starvation and disease plaguing their country. These refugees, crowding unavoidably into the most insalubrious accommodation British towns and cities had to offer, were soon blamed for deadly outbreaks of epidemic typhus which emerged across the country during the first half of 1847. Indeed, they were accused of transporting the pestilence, then raging in Ireland, over with them. Typhus mortality rates in Ireland and Britain soared, and so closely connected with the disease were the Irish in Britain that it was widely referred to as ‘Irish fever’. Much of what we know about this epidemic is based on a handful of studies focusing almost exclusively on major cities along the British west-coast. Moreover, there has been little attempt to understand the legacy of the episode on the Irish in Britain. Taking a national perspective, this article argues that the ‘Irish fever’ epidemic of 1847 spread far beyond the western port of entry, and that the epidemic, by entrenching the association of the Irish with deadly disease, contributed significantly to the difficulties Britain's Irish population faced in the 1850s.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| 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".