Bibliographic record
Abstract
A former revolutionary Scotsman achieves prosperity in New York through hard work and social networking Scholarly edition that distinguishes the 1832 text from the 1830 texts and presents it with a glossary of Scottish terms and historical notes Introduction that examines Galt’s techniques for combining fiction with lived experience and that provides contextual information about emigration from Scotland, political reform in Britain, and socio-economic conditions and aspirations in New York at the beginning of the nineteenth century Maps that enable readers to put together the novel’s imaginary and actual locations In Lawrie Todd (1830; rev. ed. 1832), John Galt paints an optimistic portrait of Scottish emigration to North America. Designed as a fictional autobiography, the novel charts the fortunes of its protagonist from his departure from Scotland—to avoid being tried for treason over his French Revolutionary sympathies—to his rise to prosperity as a shopkeeper in New York City and imaginary towns near Rochester. This edition of the novel provides a contextual introduction, explanatory notes and maps that connect Todd’s life story with boom times in New York and with Galt’s own efforts at social entrepreneurship in Canada as well as with debates over emigration and political reforms in Britain. It sheds light on Galt’s methods of characterisation, including his use of Scots and Yankee" speech habits and adaptation of real-life models, and on his popularity with readers in his own time. "
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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 | 0.000 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.079 | 0.017 |
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".