MétaCan
Menu
Back to cohort
Record W4380231891 · doi:10.1515/9780228015338

France in the World

2023· book· en· W4380231891 on OpenAlexaboutno aff
Sean M. Kennedy

Bibliographic record

VenueMcGill-Queen's University Press eBooks · 2023
Typebook
Languageen
FieldArts and Humanities
TopicEuropean Political History Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeography

Abstract

fetched live from OpenAlex

André Siegfried (1875–1959) was a leading figure in French academic and cultural life for over five decades. A world traveller who trained as a geographer, Siegfried became a leading political scientist and prominent newspaper columnist. As a long-time professor at Sciences Po, he shaped generations of his country’s elite. France in the World explores the life and career of André Siegfried. An innovator in the field of political science, he established himself as France’s leading interpreter of the English-speaking world. Often likened to Alexis de Tocqueville, Siegfried published influential studies of the United States, Canada, Great Britain, and New Zealand, striving to understand France’s place in a changing global context. Siegfried was a cosmopolitan promoter of liberalism and individual freedom. But at the same time he perceived France to be the core of a Western civilization whose leadership and values were threatened by Americanization, anti-imperial nationalism, and non-white immigration. By following Siegfried’s long career and examining the breadth of his writings, Sean Kennedy shows how his racial and ethnic essentialism was a unifying aspect of his life’s work. That these ideas were considered unremarkable for most of his lifetime offers a powerful illustration of how racist thinking permeated mainstream French republicanism. Exploring the many facets of Siegfried’s career, France in the World examines the entanglement of liberal and racist thinking during an era that witnessed political extremism and a rapidly changing international order.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.844
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.203
Teacher spread0.177 · 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 teacher head, not a consensus.

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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueMcGill-Queen's University Press eBooksSame topicEuropean Political History AnalysisFrench-language works237,207