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Record W2801700534 · doi:10.7202/1044158ar

« Too many sorry business ». Mort et rites funéraires dans le désert occidental australien

2018· article· fr· W2801700534 on OpenAlexaffvenue
Sylvie Poirier

Bibliographic record

VenueFrontières · 2018
Typearticle
Languagefr
FieldSocial Sciences
TopicVietnamese History and Culture Studies
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Depuis plusieurs décennies déjà, le taux de mortalité dans les communautés aborigènes dites isolées du centre et du nord de l’Australie est assez élevé. Les causes sont diverses : mauvais état de santé, alcoolisme, accidents de voiture et violence. Tant et si bien que les Aborigènes sont constamment engagés dans ce qu’ils appellent en anglais le sorry business, soit les rites de lamentation et de deuil. En 2013, un séjour dans la communauté aborigène de Balgo (désert occidental australien), où je mène des recherches depuis 1980, m’a à nouveau confirmé cette réalité. Alors que la messe funéraire est prise en charge par l’Église catholique, les sorry business débutent dès l’annonce de la mort et se déroulent souvent sur plusieurs semaines. Dans cet article, j’explique, d’une part, la conception aborigène de la mort et décris les rites mortuaires contemporains. J’interroge, d’autre part, le comment et le pourquoi de ce haut taux de mortalité au sein de l’État-Nation australien lequel, tout en misant sur la « normalisation » des Aborigènes, continue à nier leur différence.

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 score0.292
Threshold uncertainty score0.581

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 studies0.0070.006
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0010.002
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 head0.019
GPT teacher head0.294
Teacher spread0.275 · 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

Citations0
Published2018
Admission routes2
Has abstractyes

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Same venueFrontièresSame topicVietnamese History and Culture StudiesFrench-language works237,207