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Record W7139220235

The literary imaginary of Polynesia in the nineteenth century : a history of metamorphosis (France, United Kingdom, USA)

2019· article· fr· W7139220235 on OpenAlexaboutno aff
Abdel Rahman Alnatsheh

Bibliographic record

Venuetheses.fr (ABES) · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicPacific and Southeast Asian Studies
Canadian institutionsnot available
Fundersnot available
KeywordsThe ImaginaryColonialismColonial periodCannibalismBattle
DOInot available

Abstract

fetched live from OpenAlex

Cette thèse traite de l’évolution des modes de représentations et de l’image du Polynésien dans les littératures française, anglaise et américaine depuis 1842, la date du Protectorat de Tahiti, jusqu’en 1911, la période qui précède la Première Guerre mondiale. Il s’agit d’une lecture postcoloniale analysant l’influence des facteurs temporels et culturels des voyageurs occidentaux sur l’image de l’Autre et sur sa transformation du bon sauvage ou du cannibale païen en métis tiraillé entre les traditions et la modernité. Cette analyse a pour ambition de tracer la métamorphose qui marque le discours occidental sur la Polynésie et qui atteint son paroxysme à partir de la fin du XIXe. Il est question de tracer les origines de cette métamorphose, son impact sur la littérature et de déterminer si cette évolution dans le discours colonial représente une prise de conscience de l’Autre ou bien s’il s’agit des symptômes avant-coureurs d’un état de décadence qui frapperait la littérature coloniale.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.384
Threshold uncertainty score0.764

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.006
Scholarly communication0.0040.002
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.032
GPT teacher head0.272
Teacher spread0.240 · 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
Published2019
Admission routes1
Has abstractyes

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