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Record W2020298567 · doi:10.1080/0141987022000009403

Theorizing citizenship in British settler societies

2002· article· en· W2020298567 on OpenAlexaboutno aff
David Pearson

Bibliographic record

VenueEthnic and Racial Studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicMigration, Refugees, and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsCitizenshipMulticulturalismPoliticsSociologyDominionImmigrationGender studiesEthnic groupNational identityPluralism (philosophy)Identity (music)State (computer science)Political scienceLawAnthropology

Abstract

fetched live from OpenAlex

This article discusses citizenship in states with a history as British 'dominion' settler societies, focusing on questions of ethnicity and national identity. After noting the shortcomings of T. H. Marshall's widely used citizenship model, the key differences between English and British settler society citizenship experience are outlined, drawing on illustrative material from Australia, New Zealand, and Canada. The main settler/English state differences highlighted, are the presence of aboriginal peoples with distinct juridicial and political statuses; a characteristic set of relationships between successive flows of British migrants and subsequent generations of local-born settlers, and the shift in societies of immigration towards more extensive forms of ethnic and national pluralism within a 'post-settler' conception of multicultural nationhood in a globalized world. Finally, the article suggests settler and post-settler society citizenship is best conceptualized and described by examining the linked processes of what is called the aboriginalization (of aboriginal minorities), the ethnification (of immigrant minorities) and the indigenization (of settler majorities).

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.164

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.037
Scholarly communication0.0060.004
Open science0.0010.006
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.104
GPT teacher head0.367
Teacher spread0.263 · 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

Citations63
Published2002
Admission routes1
Has abstractyes

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