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Record W2275198510 · doi:10.1111/cars.12090

John Porter Lecture: Liberal Nationalisms Revisited

2016· article· fr· W2275198510 on OpenAlexaboutno aff
James Kennedy

Bibliographic record

VenueCanadian Review of Sociology/Revue canadienne de sociologie · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicPolitical Systems and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesEthnologyArtSociology

Abstract

fetched live from OpenAlex

Liberal Nationalisms: Empire, State and Civil Society in Scotland and Quebec argues that the emergence and character of nationalism are directly related to changes in patterns of political rule and the liberal settlements that underlay that rule. The focus is on the emergence of two nationalist groups in Scotland and Quebec at the beginning of the twentieth century: the Young Scots' Society and Ligue nationaliste canadienne. They exhibited liberal nationalisms differently (1) in response to the British Empire's predatory imperial policies, (2) in the perception that their states had failed to effectively accommodate the Scottish and French Canadian nations, and more problematically (3) on the place of organized religion in civil society. Their responses suggest the emergence of two quite distinct liberal nationalisms: one in which the emphasis was on universal individual rights, and the other in which particular group rights were more clearly favored. The article offers some further reflection on the relationship between nationalism and liberalism, specifically on the existence of a symbiotic relationship and more generally that liberalism is successful when embedded in nationalism.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.408
Threshold uncertainty score0.812

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0060.018
Scholarly communication0.0060.007
Open science0.0010.002
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0050.001

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 head0.039
GPT teacher head0.283
Teacher spread0.245 · 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 designTheoretical or conceptual
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

Citations2
Published2016
Admission routes1
Has abstractyes

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