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Record W7116729927 · doi:10.35784/odk.7937

Revitalising Fontecchio: a community-led approach to heritage conservation and cultural regeneration

2025· article· pl· W7116729927 on OpenAlexaff
Caterina Ruscio, Francesca Spadolini

Bibliographic record

VenueProtection of cultural heritage · 2025
Typearticle
Languagepl
FieldArts and Humanities
TopicCultural Heritage Management and Preservation
Canadian institutionsFrancophone University Association
Fundersnot available
KeywordsCultural heritageCitizen journalismCultural heritage managementIndustrial heritageDemocracyRegeneration (biology)Intangible cultural heritageParticipatory action research

Abstract

fetched live from OpenAlex

This paper examines the post-earthquake recovery and cultural regeneration of Fontecchio, a medieval village in L’Aquila, Italy, through a community-led approach to heritage conservation. Fontecchio was the first Italian municipality to adopt the principles of the Faro Convention, emphasizing democratic participation and the recognition of cultural heritage as a living resource. Drawing on direct site engagement, participatory workshops, and documentary analysis, this study investigates how local communities contribute to the preservation of tangible and intangible heritage, including traditions such as the Festa della Perdonanza. Findings demonstrate that community involvement not only facilitates the physical reconstruction of the village but also reinforces social cohesion, cultural identity, and sustainable territorial development. This case illustrates the potential of participatory heritage strategies to generate both practical and theoretical insights for heritage-led recovery in rural and post-disaster contexts.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.648
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0010.002
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.108
GPT teacher head0.278
Teacher spread0.169 · 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 teacher head, not a consensus.

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
Published2025
Admission routes1
Has abstractyes

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