Brian Moore’s Unsettling Irish Immigrant: <i>The Luck of Ginger Coffey</i>
Bibliographic record
Abstract
This essay recuperates Brian Moore’s mostly forgotten classic of Canadian immigrant fiction, The Luck of Ginger Coffey (1960), in a reading of its protagonist as a study in the necessary self-renovation of a new Canadian. Employing the scholarly work that has been done on the Irish in Canada over the past few decades, this essay contextualizes its reading of Moore’s mid-century novel in a mildly corrective history of Irish immigration to that point. Ginger Coffey will also be seen to prefigure—on the eve of Canada’s officially becoming the much-admired multicultural nation it is today—the central question facing Canadians respecting immigration. The unaccommodating setting of Ginger Coffey, its historical contexts, and its compromising immigrant’s (Ginger Coffey’s) hard-won promise of eventual integration into Canadian society challenge readers to entertain questions about the extent of Canada’s tolerance of immigrants’ tenaciously mistaken dreams.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.029 | 0.016 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".