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Record W2766895282 · doi:10.7202/1041590ar

Médiation culturelle pour la sauvegarde et la valorisation du patrimoine tunisien

2017· article· fr· W2766895282 on OpenAlexaffvenue
Selma Zaiane-Ghalia

Bibliographic record

VenueEthnologies · 2017
Typearticle
Languagefr
FieldSocial Sciences
TopicPolitical and Social Issues
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsPolitical scienceHumanitiesArt

Abstract

fetched live from OpenAlex

Depuis son indépendance, la Tunisie a consacré des efforts importants à la valorisation du patrimoine culturel dans un objectif de développement économique misant sur le secteur touristique. Les diverses institutions gouvernementales concernées par la sauvegarde et la valorisation des richesses patrimoniales, telles que le ministère de la Culture et le ministère du Tourisme, ont mis en place plusieurs actions de médiation culturelle à cet effet. De nombreux rapports et publications mentionnent ces données mais l’on a peu écrit sur l’apport important des citoyens et des organisations communautaires à ce domaine de la médiation culturelle. Or le mouvement associatif a toujours été fort en Tunisie et il s’est renforcé depuis la révolution de 2010. À partir de visites et de rencontres personnelles effectuées sur le terrain et complétées par des données récentes colligées sur Internet – sur des blogues, des pages sociales ou des sites plus professionnels –, nous nous proposons d’examiner la place de la participation citoyenne dans la médiation culturelle en Tunisie. Nous prendrons à cet effet des exemples de projets concrets.

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)0.004
metaresearch head score (Gemma)0.006
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: Empirical
Teacher disagreement score0.120
Threshold uncertainty score0.239

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0070.003
Scholarly communication0.0090.004
Open science0.0010.004
Research integrity0.0020.002
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 head0.041
GPT teacher head0.367
Teacher spread0.325 · 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

Citations1
Published2017
Admission routes2
Has abstractyes

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