Rediscovering Migration and Cultural Interaction in the ‘Old World’: Canadian Research Approaches Reach Europe
Bibliographic record
Abstract
The insertion of the memory of migration into Canadian history and the rediscovery of intra-European migrations in both statewide and pan-European versions of history have followed peculiar trajectories. The ‘country of immigration’- trope has, of course, always been present in Canadian public discourse, politics and historiography. However, in a state in which every person was equal before the law, not only did two rather than one particularly large ethnic groups claim special consideration as ‘nation’ (or ‘founding nation’); also, immigrants could not join either of the ‘nations’ but were slotted as ‘ethnics.’ In Europe, the migrations of Teutons and Saxons were recorded; so were the German-language (not: ‘German’) eastward migrations, as well as emigration; but thereafter – according to the master narrative – peoples had been sedentary for centuries. As long as these views prevailed, there was little ‘Europe’ might learn from ‘Canada’ – referring to the cultural-societal structures and practices that came into being only from the 1960s (Canada) or later (Europe). Of the two competing cultural elites one – or at least its Ontario and Maritimes section – was mentally focussed on Great Britain to the 1950s. The English-, Scottish-, and Irish-origin inhabitants in the West were somewhat skeptical of this colony-style transatlantic mental dependency. And many inhabitants of British Columbia, in fact, looked across the Pacific. The other elite, Quebec’s spokespersons (spokes men would still be an empirically correct designation), was, to some degree, as enamored with France though this relationship was complex. The clerical segment of the francophones had constructed Quebec as a new, true France after what they considered the deviousness, un-Frenchness of the Commune, industrialization, and urbanization. It is a highly problematic aspect of our languages (‘mother tongues’) that names, ‘Canada’ and ‘Europe’ in our case, apply indiscriminately to very different societal formations and to shifting geographies. Temporal, historical, change is not reflected in the words we use; neither are changing institutional settings or geographical contraction and expansion. We would need proc essual concepts, ‘scapes’ (Appadurai, Roberts), and meanings. (But this issue would merit a paper of its own.) These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.012 | 0.022 |
| Science and technology studies | 0.048 | 0.025 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 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".