Bibliographic record
Abstract
Abstract: Immigration to and through central Canada increased substantially in the middle decades of the nineteenth century. In response to some of the problems associated with this mass migration, and in an effort to stimulate more of the ‘right’ kind of settlement, state-funded immigration agencies were established at all major ports and urban reception centres across the region during this period. To date, most of the literature on this subject has focused upon the state's management of migrants in Lower Canada (at Montreal, Quebec, and Grosse-Île) and upon the response of government officials to the period's major epidemics (cholera and typhus). This article uses Toronto as a case study to trace the evolution of the state's interaction with migrants from a different starting point. It emphasizes the importance of the 1820–80 period – a period in which major state initiatives were put in place to regulate the flow of immigration more effectively. It underlines the fact that the state consisted of multiple, frequently competing layers of authority and power during the period of transition from colonies to nation. Finally, the study of Toronto highlights that the intersections of different state levels (municipal, provincial, imperial, federal) did not constitute an especially monolithic state regulatory response during this period, but rather more of a labyrinth whose changing features could radically affect the individual experiences of migrants during these years.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".