Bibliographic record
Abstract
The essays collected in offer close analysis of an array of cultural representations of the Canada-US border, in both site-specificity and in the ways in which they reveal and conceal cultural similarities and differences. Contributors focus on a range of regional sites along the border and examine a rich variety of expressive forms, including poetry, fiction, drama, visual art, television, and cinema produced on both sides of the 49th parallel. The field of border studies has hitherto neglected the Canada-US border as a site of cultural interest, tending to examine only its role in transnational policy, economic cycles, and legal and political frameworks. Border studies has long been rooted in the US-Mexico divide; shifting the locus of that discussion north to the 49th parallel, the contributors ask what added complications a site-specific analysis of culture at the Canada-US border can bring to the conversation. In so doing, this collection responds to the demands of Hemispheric American Studies to broaden considerations of the significance of American culture to the Americas as a whole -- bringing Canadian Studies into dialogue with the dominantly US-centric critical theory in questions of citizenship, globalisation, Indigenous mobilisation, hemispheric exchange, and transnationalism.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.066 | 0.034 |
| Scholarly communication | 0.020 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.002 | 0.005 |
| 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".