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Early Colonial Periodicals in Nineteenth-Century Canada: The Literary Garland in Context

2024· book-chapter· en· W4410890453 on OpenAlexaboutno aff
Fariha Shaikh

Bibliographic record

VenueEdinburgh University Press eBooks · 2024
Typebook-chapter
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismHistoryContext (archaeology)LiteratureArt historyArtArchaeology

Abstract

fetched live from OpenAlex

This piece examines the crucial role that periodical culture played in fashioning nineteenth-century Canadian identities as they emerged and developed over the course of the century. It focuses on the Montreal-based Literary Garland (1831–1851), edited by the Irish emigrant James Lovell, as one of the leading examples of periodicals that influenced notions of Anglophone ‘Canadian’ identity. It then moves on to argue that the inclusion of content such as Susannah Moodie’s initial sketches for Roughing it in the Bush in the Garland can be understood to be the beginnings of an interest in tales of local colour. The chapter situates the Literary Garland alongside its other predecessors and successors, such as the Scribbler (1821–27), and the British Colonist (1858–1910), examining the ways in which these periodicals shaped and defined notions of middle-class Canadian readerships. Thus, in tracing a long genealogy of Canadian periodicals over the course of the nineteenth century, while focussing on the Literary Garland, this piece demonstrates the importance of the periodical marketplace in driving its authors and audiences to engage with the question of what constituted ‘Canadian’ identities and ‘Canadian’ content.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.144
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.008
Science and technology studies0.0370.021
Scholarly communication0.0140.002
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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.

Opus teacher head0.015
GPT teacher head0.206
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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