Bibliographic record
Abstract
The United States is accustomed to accepting waves of migrants who are fleeing oppressive conditions and political persecution in their home countries. But in the 1960s and 1970s, the flow of migration reversed as over fifty thousand Americans fled across the border to Canada to resist military service during the Vietnam War or to escape their homeland’s hawkish society. Unguarded Border tells their stories and, in the process, describes a migrant experience that does not fit the usual paradigms. Rather than treating these American refugees as unwelcome foreigners, Canada embraced them, refusing to extradite draft resisters or military deserters and not even requiring passports for the border crossing. And instead of forming close-knit migrant communities, most of these émigrés sought to integrate themselves within Canadian society. Historian Donald W. Maxwell explores how these Americans in exile forged cosmopolitan identities, coming to regard themselves as global citizens, a status complicated by the Canadian government’s attempts to claim them and the U.S. government’s eventual efforts to reclaim them. Unguarded Border offers a new perspective on a movement that permanently changed perceptions of compulsory military service, migration, and national identity.
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 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.025 | 0.005 |
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".