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Record W2900675759 · doi:10.4000/ideas.4330

Écrire l’histoire du Québec pour les touristes

2018· article· fr· W2900675759 on OpenAlexaboutno aff
Serge Jaumain

Bibliographic record

VenueIdeAs · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicCultural Identity and Heritage
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical science

Abstract

fetched live from OpenAlex

Les guides touristiques imprimés constituent un outil essentiel dans l’élaboration des savoirs géographiques, artistiques, culturels, sociaux, mais aussi politiques et historiques, des millions de visiteurs qui, chaque année, foulent le sol québécois. En quelques pages, ils offrent une introduction à un nouvel univers et participent ainsi à la construction des représentations collectives. Leur impact a pourtant longtemps été ignoré par les historiens. Ce texte propose les premiers résultats d’une étude des présentations historiques du Québec dans une septantaine de guides touristiques publiés en français ou en anglais entre 1963 et 2016. Après avoir examiné la manière dont ces textes sont construits, l’étude montre qu’au cours de la période considérée le discours évolue peu, excepté sur deux points : les autochtones et la question nationale. Pour les premiers, la présentation se veut de plus en plus attentive à leur situation socio-économique, et leur place dans le récit historique bénéficie d’une progressive revalorisation. La question nationale constitue pour sa part l’élément central de nombreuses introductions historiques reflétant ainsi les interrogations des voyageurs face à la revendication autonomiste du Québec. C’est surtout l’un des rares endroits où certains guides s’éloignent de leur neutralité traditionnelle pour formuler quelques jugements sur le mouvement autonomiste ou, plus généralement, sur les relations entre anglophones et francophones.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.057
Threshold uncertainty score0.415

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0150.006
Scholarly communication0.0060.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0220.002

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 head0.026
GPT teacher head0.222
Teacher spread0.196 · 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
GenreOther

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 routes1
Has abstractyes

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