Moments of Nationalism: Global and Local Intersections in Canadian Literature
Bibliographic record
Abstract
Abstract: As the strength of nation-states seems to have declined in the face of globalizing forces and modern discourses which disavow the fixity of their frontiers, the question emerges whether national identification is vanishing alongside the structures that support it. Certainly, the exclusivist restrictions and homogenizing tendencies inherent to nationalism must be redressed in order to accommodate the socio-cultural transformations that are taking place in an increasingly borderless world. In terms of emotional attachment, however, it cannot be denied that the nation provides one of the most salient contexts in which to locate notions of belonging and identity constructions. This paper offers a literary analysis of Jean McNeil’s novel The Interpreter of Silences, in order to illustrate the phenomenon I call “moments of nationalism”. I argue that, rather than disappearing altogether, national identification materializes temporarily in strategic individual and collective positionings. As overarching national narratives fail to incorporate the multiplicity of cultures and identities they intend to encompass, nationalism can no longer be read as a permanent, stable identity marker. Moments of nationalism are, on the contrary, ephemeral, and their articulation is mediated by intersections with the intranational context of the local-regional and the transnational context of the global.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.040 | 0.031 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| 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".