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Record W2882970502 · doi:10.1177/0759106318778827

Étudier les blogueurs politiques en France

2018· article· fr· W2882970502 on OpenAlex
Marie Neihouser

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

VenueBulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique · 2018
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

Qui sont les blogueurs et blogueuses politiques français·es ? L’objectif de cet article est de construire un corpus rassemblant l’ ensemble des blogs politiques en France afin de pouvoir sociologiser leurs auteurs. Cette quête d’exhaustivité est ici abordée comme un problème de méthode en tant que tel. Je montre que les méthodes propres à la sociologie classique, et plus particulièrement l’identification des positions sociales des individus, sont non seulement adaptables, mais dans certains cas nécessaires au terrain numérique. En effet, en choisissant d’étudier la position sociale des blogueurs/gueuses, je suis non seulement en mesure de rapporter leurs activités en ligne à leur existence hors-ligne, mais je prouve surtout que l’espace des blogs politiques reste en France très imbriqué dans les champs politique et médiatique traditionnels.

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)0.027
metaresearch head score (Gemma)0.069
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.624
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0270.069
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0000.000
Science and technology studies0.0020.028
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0050.004
Insufficient payload (model declined to judge)0.0550.002

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 head0.271
GPT teacher head0.408
Teacher spread0.137 · 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