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Record W4409476035 · doi:10.7202/1117429ar

« Chaque enfant compte »

2024· article· fr· W4409476035 on OpenAlexaffvenueabout
Marie-Pierre Bousquet

Bibliographic record

VenueAnthropologie et Sociétés · 2024
Typearticle
Languagefr
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMedicine

Abstract

fetched live from OpenAlex

Mai 2021 : à Kamloops, en Colombie-Britannique, les médias annoncent que les restes de 215 enfants sont repérés au géoradar sur le terrain d’un ancien cimetière à côté de ce qui fut un pensionnat indien. Cet événement déclenche, parmi la population canadienne, un tollé qui a un écho international. Pendant plusieurs semaines, l’indignation est vive, le public réclamant des explications, d’autant que d’autres découvertes similaires suivent. Cet article analyse les enjeux derrière ces événements, ainsi que les débats suscités par le fait qu’aucun reste humain n’a été exhumé et montré. Que sait-on de ces enfants et de leur décès ? Dans quelles conditions sont-ils morts ? Sont-ils vraiment morts à cause des pensionnats et des politiques qui y étaient associées ? Leurs morts sont-elles « normales » ou « anormales » ? Ont-ils eu des funérailles ? Nous verrons que ces tombes imperceptibles ont remis en question le narratif de l’histoire canadienne.

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)0.002
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 score0.118
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0070.005
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0120.002

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 head0.274
GPT teacher head0.650
Teacher spread0.376 · 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
Published2024
Admission routes3
Has abstractyes

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