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Record W2423320185 · doi:10.5401/healthhist.14.1.0121

Colonised and Neurasthenic: <em>From the Appropriation of a Word to the Reality of a</em> Malaise de Civilisation <em>in Urban French Vietnam</em>

2012· article· en· W2423320185 on OpenAlexaff
Laurence Monnais

Bibliographic record

VenueHealth and History · 2012
Typearticle
Languageen
FieldArts and Humanities
TopicHistorical Studies and Socio-cultural Analysis
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsNeurastheniaCivilizationAppropriationColonialismHistoryContext (archaeology)ModernityMalaiseSociologyEthnologyMedicinePhilosophyPsychiatryEpistemology

Abstract

fetched live from OpenAlex

Neurasthenia remains an important health problem in certain Asian populations, both in Asia as well as in a diasporic context. An anachronistic disease for Western observers, it has become an exotic culture-bound syndrome as well as a somatoform disorder too often hiding much more serious issues of depression. This article approaches this 'problematic' health issue from a historian's point of view and offers a colonial genealogy that will discuss neurasthenia's outline in French Vietnam. By retracing and analysing the different mentions, definitions, and uses of the term neurasthenia in the interwar period, it aims to better understand certain historical realities that might have shaped the local identity and spatiality of this problem (concentrated in colonial cities in which social change and modernity were expressed in their most salient forms), and perhaps even identify reasons that facilitated its post-colonial survival.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.332

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.008
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.234
Teacher spread0.202 · 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 designQualitative
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

Citations9
Published2012
Admission routes1
Has abstractyes

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