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Record W2583643516 · doi:10.4000/vertigo.17927

Vulnérabilité et adaptation des sociétés littorales aux aléas météo-marins entre Guérande et l'île de Ré, France (XIVe - XVIIIe siècle)

2016· article· fr· W2583643516 on OpenAlexvenueno aff
Emmanuelle Athimon, Mohamed Maanan, Thierry Sauzeau, Jean-Luc Sarrazin

Bibliographic record

VenueVertigO · 2016
Typearticle
Languagefr
FieldSocial Sciences
TopicMigration, Health, Geopolitics, Historical Geography
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Cette recherche se propose d'explorer la notion de vulnérabilité des sociétés littorales médiévales et modernes de l'Ouest de la France face aux crises engendrées par des événements exceptionnels. Le cadre spatio-temporel de l'étude est localisé en France, de la presqu'île guérandaise à l'île de Ré, entre le xive et le xviiie siècle. Cette zone littorale sensible, voire éminemment fragile par endroits, est régulièrement battue par des vents violents et subit des submersions épisodiques susceptibles d'engendrer des ruptures d'équilibre. Interroger la notion de vulnérabilité socio-spatiale dans une perspective historique a en premier lieu exigé d'identifier les aléas. Le choix fut fait de s'intéresser principalement à ceux liés au vent (tempêtes) et à la mer (submersions). L'étude des impacts de ces phénomènes sur les sociétés, ainsi que l'analyse de leurs réactions a ensuite permis d'aborder en simultané la vulnérabilité et les formes d'adaptation des populations littorales anciennes, en particulier à travers la mise en mémoire, la conscience du risque, le développement de la prévention, etc. Penser la notion de vulnérabilité sur le temps long contraint l'historien à se positionner à la croisée entre facteurs naturels, perceptions mentales, aménagements et décisions politiques.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.198
Threshold uncertainty score0.395

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.002
Scholarly communication0.0020.001
Open science0.0000.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.046
GPT teacher head0.346
Teacher spread0.300 · 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 designObservational
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

Citations15
Published2016
Admission routes1
Has abstractyes

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Same venueVertigOSame topicMigration, Health, Geopolitics, Historical GeographyFrench-language works237,207