Bibliographic record
Abstract
B orders in Globalization, a multi-disciplinary and international research program, funded through a SSHRC Partnership Grant and the European Union's Jean Monnet Program with colleagues across Canada and in 15 different countries, collected data on borders since 2012.Our core research focus was to challenge the well-established conception that borders are primarily understood as sovereign territorial boundaries that emerge out of international treaties.The research program thus addressed fundamental how, why, and what questions about borders, a very important contribution to knowledge in a globalizing world when movement is increasingly scrutinized everywhere, and not just at the sovereign boundary line of states, and at a time, when goods seem to travel more easily than humans.Indeed, the regulation of human flows across borders is fraught and highly contentious, and even today humans die crossing borders in the thousands yearly.Our team studied border history and culture, mobility and security, environmental sustainability and governance.As illustrated by this book, and a number of other books published with BIG_Books and the University of Ottawa Press series on Borders in Globalization, our research program initially approached those questions from the perspective of territories, regions, and states, to collect evidence that there were multiple challenges to the "territorial trap" assumption.In Borders and Migration: The Canadian Experience in Comparative Perspective Michael Carpenter, Melissa Kelly, and Oliver Schmidtke have edited a volume comprising 12 chapters, an introduction, and a conclusion, which carefully review, document, and analyze how Canadian borders and immigration policies are increasingly intertwined.They look at the governance of human mobility in comparative perspective with the policies of the European Union, Japan, Mexico,
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.460 | 0.306 |
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".