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Record W4324319049 · doi:10.1017/9781009207683

<I>Marché Noir</I>

2023· book· en· W4324319049 on OpenAlexaff
Kenneth Mouré

Bibliographic record

VenueCambridge University Press eBooks · 2023
Typebook
Languageen
FieldArts and Humanities
TopicFrench Historical and Cultural Studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGermanLegitimacyMemoirContext (archaeology)Black marketRealmExploitPoliticsPolitical sciencePower (physics)EconomyPolitical economyEconomic historyHistorySociologyEconomicsLawComputer security

Abstract

fetched live from OpenAlex

Kenneth Mouré shows how the black market in Vichy France developed not only to serve German exploitation, but also as an essential strategy for survival for commerce and consumers. His analysis explains how and why the black market became so prevalent and powerful in France and remained necessary after Liberation. Marché Noir draws on diverse French archives as well as diaries, memoirs and contemporary fiction, to highlight the importance of the black market in everyday life. Vichy's economic controls set the context for adaptations – by commerce facing economic and political constraints, and by consumers needing essential goods. Vichy collaboration in this realm seriously damaged the regime's legitimacy. Marché Noir offers new insights into the dynamics of black markets in wartime, and how illicit trade in France served not only to exploit consumer needs and increase German power, but also to aid communities in their strategies for survival.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.471
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
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 head0.037
GPT teacher head0.182
Teacher spread0.145 · 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
GenreOther

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

Citations7
Published2023
Admission routes1
Has abstractyes

Explore more

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