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Record W3094054041 · doi:10.3828/bjcs.2020.2

Lady Aberdeen and the British origins of multiculturalism in Canada

2020· article· en· W3094054041 on OpenAlexaboutno aff
Amy Shaw, Andrew Smith

Bibliographic record

VenueBritish Journal of Canadian Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsMulticulturalismGender studiesNationalismEthnic groupWifeHegemonyDiversity (politics)FeminismGeneral partnershipSociologyEthnic nationalismPolitical scienceLawPolitics

Abstract

fetched live from OpenAlex

Scholarly focus on British representatives in nineteenth-century Canada has often seen them as enforcers of a hegemonic English ethnic nationalism. This article challenges that view by showing that Lady Aberdeen, the wife of the seventh Governor General, and well known as an early feminist, was also a consistent advocate of a more pluralistic civic nationalism that supported minority religious, ethnic, and linguistic rights in Canada. It shows that her establishment of the Victorian Order of Nurses and Canada’s branch of the National Organisation of Women, along with many of her activities in partnership with her husband, were shaped by her beliefs about religious and ethnic co-existence as well as her feminism and anti-Americanism. In doing so it connects acceptance of diversity with longer-term trends in British governance: Lady Aberdeen’s approach to cultural and religious diversity within women’s organisations was an important precursor of official multiculturalism in Canada.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.179
Threshold uncertainty score0.952

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0470.017
Scholarly communication0.0080.002
Open science0.0010.005
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0080.000

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 head0.021
GPT teacher head0.224
Teacher spread0.203 · 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
Published2020
Admission routes1
Has abstractyes

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