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Record W2939961065 · doi:10.3167/hrrh.2018.440304

The Battle of the Mountains

2018· article· en· W2939961065 on OpenAlexvenueno aff
Christine Haynes

Bibliographic record

VenueHistorical Reflections/Réflexions Historiques · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicHistorical and Literary Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBattleGloryCONTESTContext (archaeology)HistoryBoomArtAestheticsAncient historyArchaeologyEngineeringPolitical scienceLaw

Abstract

fetched live from OpenAlex

At the beginning of the Second Restoration, Paris was swept by a mania for roller coasters, which were dubbed montagnes russes after a Russian tradition of sledding on ice hills. Situating this phenomenon in the context of the military occupation of France following the defeat of Napoleon, this article analyzes one of the many plays featuring these “mountains,” Le Combat des montagnes (“The Battle of the Mountains”), and especially two of its main characters, La Folie (Folly) and Calicot (Calico Salesman). The “battle” over the roller coasters, it argues, was really a contest over how to redefine national identity around consumer culture rather than military glory. Through the lens of the montagnes russes, the article offers a new perspective on the early Restoration as an aftermath of war.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0090.014
Scholarly communication0.0050.002
Open science0.0000.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.342
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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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