Cornelius J. Jaenen, Promotors, Planters, and Pioneers: The Course and Context of Belgian Settlement in Western Canada
Bibliographic record
Abstract
Like his subject, the Belgians of West Canada, the author has found plenty of new ground to till.Indeed, this is the most in-depth look at the individual lives of Canadian Belgians available, and supersedes in that regard Dirk Musschoot's Wij gaan naar Amerika.Vlaamse landverhuizers naar de Nieuwe Wereld 1850-1930 (Tielt 2002).Jaenen's thesis is that Belgians in Canada lacked 'institutional completeness' and 'ethnolinguistic homogeneity' which led to a 'partialized or fragmented ethnicity'.While Jaenen presents an impressive amount of data mined from files of the Belgian National Archives, he leaves many questions unanswered.To summarize, the author explains that the Canadian Government deemed Belgians a preferred immigrant group, but that they were not heavily recruited, nor did they settle in ethnic blocs.Rather, Belgians in West Canada settled in dispersed agricultural communities, first in the 1880s outside of Winnipeg.At this time, agrarian discontent in Belgium, particularly the collapse of the grain market, led Belgian farmers to seek work elsewhere.Most migrated locally and regionally, especially to France.Belgians came to Canada in three waves: 1) 16,000 immigrants from 1890 to 1914, 2) 14,000 from 1919 to 1939, and 3) 35,000 from 1945 to the 1980s.The few Belgian farmers in the Canadian West worked in dairy, raised sugar beets and wheat.By 1900, they also worked as miners and farmers in Alberta and British Columbia.The author believes he has taken an uncommon tack by shifting his gaze away from the traditional push-pull factors of migration and towards topics of immigrant life and assimilation in Canada.He would be wise to recognize, however, that historians in the United States and Canada have always been more interested in the latter topics, leaving European scholars to sort out the factors which inspired trans-Atlantic migrations.What remains of the text is the kind of history popular in the first half of the twentieth century -intense descriptions of people and places, noting the successes of the immigrants and their contribution to their communities and nation.But what does a collection of individual stories tell us about the nature of a group of people?The author does not explain how well the Belgians in West Canada were connected to Belgians in East Canada, in Wisconsin or Detroit, or whether they had any
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.005 | 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".