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Empire's Legacy

2019· book· en· W4245645896 on OpenAlexaff
John W.P. Veugelers

Bibliographic record

Venuenot available
Typebook
Languageen
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsPoliticsPsychological nativismEmpireColonialismArgument (complex analysis)ModernityInterpretation (philosophy)Political scienceHistoryPolitical economyMainstreamIndependence (probability theory)GenealogySociologyLawPhilosophy

Abstract

fetched live from OpenAlex

Abstract Building on the idea of latent political potential, this book offers an alternative interpretation of the contemporary far right. Its main thesis is that relations between colonizers and colonized implanted a legacy that, under certain conditions, translated into support for the far right in France. To make this argument, the book offers a model for the study of political potentials that combines a situational approach to identity relations, a networks approach to subcultural practice, and a historical approach to political opportunity. The early part of this book traces the origins and development of this potential among the European settlers of French Algeria. The middle part examines its transmission via voluntary associations and its channeling into mainstream parties. The latter part examines the conditions under which this potential redirected into the far right. Starting with colonial Algeria, after independence in 1962 the book moves between politics at three levels: France, the southeast region, and Toulon (which in 1995 became the largest city in postwar Europe to elect a far-right administration). Complementing economic explanations for nativism, this book argues that our understanding of modernity errs when it disregards the potency of anachronistic remnants.

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)0.000
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.023
Threshold uncertainty score0.076

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.005
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0230.004

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 head0.047
GPT teacher head0.203
Teacher spread0.156 · 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
GenreOther

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

Citations11
Published2019
Admission routes1
Has abstractyes

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Same topicFrench Historical and Cultural StudiesFrench-language works237,207