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Record W4220753280 · doi:10.2478/jnmlp-2022-0003

Defining National Memories: The Cases of Popular Rebellions in Ireland and Québec

2022· article· en· W4220753280 on OpenAlexaffabout
Christophe Davis

Bibliographic record

VenueJournal of Nationalism Memory & Language Politics · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsYork University
Fundersnot available
KeywordsCollective memoryNationalismReciprocity (cultural anthropology)IrishIrish nationalismHistoriographyNational identityMythologyMemorizationSociologyCollective identityAmnesiaHistoryPolitical sciencePolitical economySocial scienceLawPsychologyPoliticsPhilosophyLinguistics

Abstract

fetched live from OpenAlex

Abstract While studies on nations and nationalism have brilliantly demonstrated the influence of collective memory on national development, few studies have examined the reciprocity of this relationship. This article is therefore concerned with the laborious processes of memorizing the founding myths of both the Irish and Québécois nations. Indeed, while today the rebellion of 1798 in Ireland and those of 1837–1838 in Québec are central to their respective processes of identity-building, it has not been a calm process; the 1798 rebellion was buried in collective amnesia for almost a century and in Québec, the Patriotes rebellions have constantly moved in and out of collective memory. I argue, in this article, that the unstable definition of both nations harmed the process of remembrance. I am therefore interested in the long and conflicting journey that has enabled the Irish and Québécois nations to define themselves, respectively, by their religion and their language. Through a historiographical analysis of the speeches from several leaders of these two nationalist movements, this article shows how nations define and redefine themselves and how memories are also altered to meet those changes.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.503

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.003
Science and technology studies0.0390.021
Scholarly communication0.0070.004
Open science0.0030.009
Research integrity0.0040.007
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 head0.030
GPT teacher head0.271
Teacher spread0.241 · 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 designQualitative
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
Published2022
Admission routes2
Has abstractyes

Explore more

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