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Record W2304482863 · doi:10.1093/fs/knu215

Narratives of the French Empire: Fiction, Nostalgia, and Imperial Rivalries, 1784 to the Present <i>Narratives of the French Empire: Fiction, Nostalgia, and Imperial Rivalries, 1784 to the Present</i> . By K <scp>ate</scp> M <scp>arsh</scp> . (After the Empire: The Francophone World and Postcolonial France.) Lanham: Lexington Books, 2014. xvii + 131 pp.

2014· article· en· W2304482863 on OpenAlexaffabout
Srilata Ravi

Bibliographic record

VenueFrench Studies · 2014
Typearticle
Languageen
FieldArts and Humanities
TopicTravel Writing and Literature
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsEmpireColonialismPoliticsHistoryNarrativeLiteratureRepresentation (politics)ArtAncient historyLawArchaeologyPolitical science

Abstract

fetched live from OpenAlex

At the intersection of literary and historical studies, Kate Marsh's monograph offers refreshing and meticulously researched insights into France's imperial pasts. Presenting an alternative perspective to current scholarly discussions on France's history of overseas expansion from the eighteenth to the twentieth century, the study locates three fictional texts representing, on the one hand, key historical moments (after 1763, after the loss of Haiti, and the inter-war period), and, on the other, different geographical locations (Tahiti, Martinique, and Pondicherry) within their ‘political, social and cultural locus of production’ (p. xii). Thereby Marsh's study examines the circulation of ideas across different colonial sites and demonstrates persuasively how perceptions of French colonialism were shaped by conflicts and compromises between rival European powers. Central to the book's thesis is the fact that imperial nostalgia, which modulates strategies of representation, was used not only to ensure that French colonialism survived but also to show that it was ‘different from that practised by the British’ (p. 36). The Introduction and first chapter set out the study's disciplinary contexts and methodological relevance succinctly and efficiently, while each of the remaining chapters is dedicated to individual novels. Marsh's methodical reading of fiction's — Mme de Monbart's Lettres taïtiennes, Louis de Meynard de Queilhe's Outre-mer, Georges Delamare's Désordres à Pondichéry — connections with perceptions of Empire published in contemporaneous journals, newspapers, political texts, and other forms of literary expression throws light on intra-European exchange in eighteenth-century Tahiti. She argues that in Martinique the proximity of British colonies makes the English ‘an obvious target of French patriotic rhetoric’ (p. 59), and establishes that nostalgic imaginings of Pondicherry in the 1930s ‘serve[d] as a synecdoche of the whole of the French Empire’ (p. 84). One of the most noteworthy aspects of this study is its historical range, which includes both periods of French expansion, one under the Ancien Régime and the other after 1830. By providing a longitudinal and comparative analysis of the selected novels, Marsh's study illustrates, most remarkably, the presence of enduring tropes in the representations of France's imperial enterprise, continuities that are perceptible up to the present day. The inclusion of literary texts from eighteenth-century Nouvelle France and Isle de France, whose histories suggest similar interactions between rival European powers, could eventually offer an interesting complement to the works studied: did Tahiti, Mauritius, and Quebec in the eighteenth century influence French imaginings of colonization in the same way? In short, Narratives of Empire is a thought-provoking work and undoubtedly a very rich and original contribution to the study of afterlives of Empire.

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)0.003
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: Review · Consensus signal: none
Teacher disagreement score0.113
Threshold uncertainty score0.225

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0100.018
Scholarly communication0.0070.004
Open science0.0010.002
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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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
GenreReview

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

Citations3
Published2014
Admission routes2
Has abstractyes

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