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Record W2949676426 · doi:10.1017/ssh.2019.23

L’éruption patriote: The Revolt against Dalhousie and the Petitioning Explosion in Nineteenth-Century French Canada

2019· article· en· W2949676426 on OpenAlexaboutno aff
Daniel Carpenter, Doris Brossard

Bibliographic record

VenueSocial Science History · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsAlliancePolitical scienceNationalismMobilizationMass mobilizationAdministration (probate law)ColonialismDemocracyEconomic historyLawHistoryPolitics

Abstract

fetched live from OpenAlex

As much as any other site in the nineteenth century, Francophone Lower Canada saw immense waves of popular petitioning, with petitions against British colonial administration attracting tens of thousands of signatures in the 1820s. The petition against Governor Dalhousie of 1827–28 attracted more than 87,000 names, making it one of the largest mass petitions of the Atlantic world on a per-capita scale for its time. We draw upon new archival evidence that shows the force of local organization in the petition mobilization, and combine this with statistical analyses of a new sample of 1,864 names from the anti-Dalhousie signatory list. We conclude that the Lower Canadian petitioning surge stemmed from emergent linguistic nationalism, expectations of parliamentary democracy, and the mobilization and alliance-building efforts of Patriote leaders in the French-Canadian republican movement. As elsewhere in the nineteenth-century Atlantic, the anti-Dalhousie effort shows social movements harnessing petitions to recruit, mobilize, and build cross-cultural alliances.

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)0.003
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: Empirical
Teacher disagreement score0.134
Threshold uncertainty score0.971

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0210.008
Scholarly communication0.0040.001
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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.

Opus teacher head0.006
GPT teacher head0.193
Teacher spread0.187 · 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

Citations15
Published2019
Admission routes1
Has abstractyes

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