MétaCan
Menu
Back to cohort
Record W3092906613 · doi:10.4000/revuehn.508

Éditorial. Donner à lire les humanités numériques francophones (1)

2020· article· fr· W3092906613 on OpenAlex
Aurélien Berra, Emmanuel Château-Dutier, Emmanuelle Morlock, Sébastien Poublanc, Émilien Ruiz, Nicolas Thély

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHumanités numériques · 2020
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

La création d’Humanités numériques s’inscrit dans un moment particulier des sciences humaines et sociales. Les révolutions proclamées et les transitions programmées font place à des évolutions collectives, qu’il nous appartient d’influencer pour qu’elles soient intelligentes et heuristiques. À l’heure où paraissent ses deux premiers numéros, la présentation générale de la revue sur OpenEdition Journals s’achève sur ces mots : « Nous publions des auteurs et acteurs prêts à objectiver, chroniquer et critiquer, au sens le plus riche du terme, l’évolution de leurs pratiques et de leur pensée. » Ce premier éditorial vise à expliciter succinctement ces intentions, l’historique du projet et les soutiens qui lui donnent les moyens de ses ambitions, tandis que l’éditorial suivant commentera le contenu de ces numéros.

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.

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), Scholarly communication, 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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.856
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0080.010
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.350
GPT teacher head0.318
Teacher spread0.033 · 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