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Des noms et des lieux : la médiation toponymique au Québec et en Arcadie du Nouveau-Brunswick

2008· dissertation· W7143282351 on OpenAlexaboutno aff
Francine Adam

Bibliographic record

Venuenot available
Typedissertation
Language
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsPossessiveContext (archaeology)OnomasticsIdentity (music)

Abstract

fetched live from OpenAlex

La médiation toponymique est l’un des ensembles relationnels qui font une terre habitée, ici le Québec et l’Acadie du Nouveau-Brunswick. Trois souches linguistiques principales y ont déployé les lieux : l’autochtone, la française, l’anglaise. Les motifs de dénomination reliés à la propriété et la fréquentation, l’appartenance et l’événement, l’expérience directe et l’honorifique fondent la résonance des noms et de la terre. Les noms de lieux constituent un héritage à vivre et à transmettre. Corps, cœur et esprit alimentent une toponymie affective et sensible qui ressortit aux visions et perceptions du milieu naturel, s’exprime par l’anthroponynie (possessive et honorifique) et la consécration culturelle, imprègne la dynamique des changements de noms. En est une illustration le débat identitaire dans le contexte des fusions municipales au Québec. La dimension spécifiquement sémantique de la toponymie affective et sensible a permis d’établir trois grandes classes thématiques : empreintes possessives et identitaires, sens et sensations, ambiances et sentiments. Des profils régionaux apparaissent au Québec et des profils de comtés en Acadie du Nouveau-Brunswick ; une toponymie des bonheurs et des malheurs se dessine. De cette mise en parallèle du Québec et de l’Acadie du Nouveau-Brunswick, il ressort des types toponymiques fortement contrastés qui témoignent de leur histoire politique respective et du rôle des autorités institutionnelles en la matière.

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 score0.073
Threshold uncertainty score0.530

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0090.013
Scholarly communication0.0070.004
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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
Published2008
Admission routes1
Has abstractyes

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