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Record W2885265885

Une école à la dérive : Essai sur le système d'éducation au Nunavik

2016· book· fr· W2885265885 on OpenAlexaboutno aff
Nicolas Bertrand

Bibliographic record

VenueÉditions du Septentrion eBooks · 2016
Typebook
Languagefr
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical scienceArt
DOInot available

Abstract

fetched live from OpenAlex

Depuis l'implantation des premieres ecoles federales au milieu du siecle dernier, le systeme d'education au Nunavik n'a cesse d'etre en crise. Absenteisme frequent, faibles resultats scolaires, decrochage important des eleves au secondaire? le portrait est, helas, familier. L'ecole echoue par ailleurs a enseigner adequatement la culture inuite, ce qui attise les critiques a son egard. Prenant appui sur son experience personnelle a titre de suppleant dans le village de Kangirsuk, Nicolas Bertrand dresse le portrait de cette ecole dont la derive a des racines profondes et complexes. Il reflechit aussi a la maniere de reformer ce systeme et demontre la difficulte de cette entreprise. Car tant et aussi longtemps que l'ecole sera percue par les Inuits, a tort ou a raison, comme un obstacle et non comme une condition de leur emancipation, sa legitimite sera contestee et sa mission, compromise. De l'education de sa jeunesse depend pourtant l'avenir du Nunavik qui, sans renier son passe, doit aussi accepter pleinement sa modernite. Nicolas Bertrand s'envole pour Kangirsuk au moment ou parait Deja, son premier roman (Hamac, 2010). Jusqu'en 2012, il sejourne dans ce village du Nunavik ou il est, l'espace de quelques mois, suppleant au primaire et au secondaire. Depuis son retour dans le sud du pays, il enseigne la philosophie au College Montmorency a Laval.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.174
Threshold uncertainty score0.349

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.011
Scholarly communication0.0070.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.303
Teacher spread0.271 · 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
Published2016
Admission routes1
Has abstractyes

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