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Record W2113079413 · doi:10.21083/nrsc.v0i6.2867

Dib et Djaout : le métier à tisser en deux temps

2013· article· fr· W2113079413 on OpenAlexaffvenue
Christiane Ndiaye

Bibliographic record

VenueNouvelle Revue Synergies Canada · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesArtPolitical scienceEthnologySociology

Abstract

fetched live from OpenAlex

A plus de trente ans d’intervalle, Le Métier à tisser de Mohammed Dib et Les Vigiles de Tahar Djaout se construisent tous deux autour de la figure du métier à tisser, instrument de travail d’un peuple qui n’en finit pas d’être dépossédé. Si, chez Dib, l’espoir subsiste que le peuple se mettra en marche pour faire en sorte que «ça changera» (164), chez Djaout la désillusion prend des accents dramatiques. La «rénovation» du métier à tisser, du pays, ne servira finalement que les intérêts des Vigiles qui s’évertuent à «défendre le pays contre son propre peuple» (1991 : 111). La grande famille unie de la nouvelle cité dictera à chacun son comportement, sa vie et sa mort, si celle-ci peut lui servir. De la lecture croisée de ces deux romans se dégage ainsi une mise en garde contre l’imaginaire du «malgré tout» dont se sert le pouvoir pour manipuler le peuple.Though published more than thirty years apart, the novels Le Métier à tisser by Mohammed Dib and Les Vigiles by Tahar Djaout are both constructed around the figure of the loom, the instrument of labour of a people apparently faced with endless dispossession. If, in Dib’s novel, hope persists that the people will take a stand so that “things change” (164), in Djaout’s novel disillusionment takes on dramatic accents. "Renovating" the loom or the country, in fact only serves the interests of the Vigils who do their utmost to “defend the country against its own people” (1991 : 111). The great united family of the new state dictates everyone’s behaviour, their life and their death, if the latter can serve its purposes. From the joint reading of these two novels emerges a warning against the fantasy of “in spite of it all” used by the authorities to manipulate its people.

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: none
Teacher disagreement score0.051
Threshold uncertainty score0.102

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0120.011
Scholarly communication0.0060.003
Open science0.0010.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.045
GPT teacher head0.312
Teacher spread0.267 · 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
Published2013
Admission routes2
Has abstractyes

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Same venueNouvelle Revue Synergies CanadaSame topicMulticulturalism, Politics, Migration, GenderFrench-language works237,207