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Record W2063390663 · doi:10.3917/hes.124.0003

Wartime mortality in Italy's Thirty Years War: The duchy of Parma 1635-1637

2012· article· fr· W2063390663 on OpenAlexaff
Gregory Hanlon

Bibliographic record

VenueHistoire économie et société · 2012
Typearticle
Languagefr
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsDalhousie University
Fundersnot available
KeywordsHumanitiesArtPolitical science

Abstract

fetched live from OpenAlex

Résumé Cette recherche prend la mesure de l’impact démographique de la guerre de Trente Ans en Italie du Nord pour la première fois, axée sur le petit duché de Parme et de Plaisance, allié de la France. Plutôt que de déterminer les dimensions de la population globale avant et après la guerre, cette étude calcule les pertes réelles parmi les soldats et les civils. Les résultats, qui restent approximatifs, révèlent que les pertes parmi les civils dépassaient de très loin celles des militaires, suite à la faim et des maladies diverses. La différence principale par rapport à l’Allemagne fut que cette mortalité d’environ 4% de la population totale était infligée dans quelques mois seulement d’occupation par l’armée espagnole.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.051
GPT teacher head0.269
Teacher spread0.218 · 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; both teacher heads agree on what is shown here.

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

Citations3
Published2012
Admission routes1
Has abstractyes

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