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Record W3007803807 · doi:10.4000/aes.2187

Michelet et La Mer

2019· article· en· W3007803807 on OpenAlexaff
Gisèle Séginger

Bibliographic record

VenueArts et Savoirs · 2019
Typearticle
Languageen
FieldPsychology
TopicPsychoanalysis and Psychopathology Research
Canadian institutionsInstitut d'Histoire de l'Amérique Française
Fundersnot available
KeywordsVitalismDarwin (ADL)PoliticsMaterialismPhilosophyNatural (archaeology)EmpireSituatedDemocracyLiteratureHistoryEpistemologyArt historyClassicsArtAncient historyLawArchaeology

Abstract

fetched live from OpenAlex

At the beginning of the 19th century, at the same moment as Lamarck and Geoffroy Saint-Hilaire contribute to a historicization of natural sciences, moral sciences are searching in natural history for a model of thought and a positivity. Michelet, an interior exile during the Second Empire, publishes several books on Nature: he is searching for a logic of the living which would allow to rethink historical evolution and progress on a large timescale. Situated in between science and literature, La Mer develops a vitalist thought which mingles archaic beliefs and modern biological knowledge. Michelet cites Lamarck, Félix Pouchet (the defender of spontaneous generation), Darwin and his corral studies. He imagines a historical transformism, founding democratic or socialist ideas on biological and geological knowledge: evolution supplants revolution. The strangeness of La Mer results from the blend of political and scientific ideas, the intertextual encounter between Darwin and Leroux, the scientific and the socialist. It results as well form a curious form of materialism, developing an idea of transcendency internal to time and matter.

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)0.003
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 score0.025
Threshold uncertainty score0.085

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0030.003
Scholarly communication0.0050.003
Open science0.0010.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0250.007

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 head0.401
Teacher spread0.364 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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