Bundling, Reprinting, and Reframing: Serial Practices Across Borders
Bibliographic record
Abstract
ABSTRACT This article explores the circulation of periodical material between metropolitan and regional locations in early twentieth-century North America. It asks how the globalized consumer technology of the household magazine was being taken up outside of cosmopolitan centers through the framework of local, regional, or national concerns. For example, mainstream Canadian monthlies such as The Western Home Monthly and Maclean's frequently engaged with, or re-used, content and formats taken from New York publications. To understand these transnational publishing dynamics, we argue, it is crucial to attend to the material practices of magazines. The article analyzes several such practices, including both editorial and sales strategies. We look at the reprinting or reframing of complete features and of excerpts from other periodicals. We examine the simultaneous serialization of novels in American and Canadian publications, using a case study of Martha Ostenso's Wild Geese. And we offer the first critical discussion of “bundling,” whereby US and Canadian titles were packaged together as a single subscription. It argues that the affordances of seriality, particularly timeliness and increased circulation through decreasing prices, allowed editors to redeploy metropolitan print materials for a regional readership eager to imagine themselves as participants in the new project of modernity.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.012 | 0.018 |
| Scholarly communication | 0.013 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".