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Record W7053296382

Vulgariser les sciences sans l’appui des savants. Jean Lanteires et le Journal de Lausanne (1786-1792)

2013· article· fr· W7053296382 on OpenAlexaboutno aff

Bibliographic record

VenueBern Open Repository and Information System (University of Bern) · 2013
Typearticle
Languagefr
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSituatedContext (archaeology)Natural (archaeology)Human scienceSociology of scientific knowledgeScientific literatureQuarter (Canadian coin)Natural science
DOInot available

Abstract

fetched live from OpenAlex

Popularizing science without the support of scholars. Jean Lanteires and the Journal de Lausanne (1786-1792). - Founded in 1786 by Jean Lanteires, the Journal de Lausanne is a widespread, weekly journal with the express aim of disseminating scientific knowledge among the lower and middle classes. Its articles are easily comprehensible and cover a wide range of topics from literature to agriculture, from natural sciences to charity. Considerable space is given to reader's questions and comments. The journal can be situated somewhere between an almanac and a scientific journal. Lanteires' attempt to solicit contributions from scholars of medicine and natural sciences received a dismissive response. Of the few articles written by specialists, the majority deal with agriculture and charity. Lanteires' difficult relationship with the scholarly community is reflected in the journal's content. This makes the Journal de Lausanne a privileged observatory for studying the social context of the vulgarization process in late-eighteenth-century Switzerland and Europe.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.579
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0010.004
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.018
GPT teacher head0.228
Teacher spread0.210 · 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 designOther design
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

Citations0
Published2013
Admission routes1
Has abstractyes

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