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MONDOUX, André et MENARD, Marc (dir.), 2018. Big Data et société. Industrialisation des médiations symboliques

2021· article· fr· W3184687439 on OpenAlexaffabout
Anja Martin-Scholz, Anne Mayère

Bibliographic record

VenueCommunication et organisation · 2021
Typearticle
Languagefr
FieldComputer Science
TopicCultural Insights and Digital Impacts
Canadian institutionsUniversité du Québec
Fundersnot available
KeywordsHumanitiesArt

Abstract

fetched live from OpenAlex

Cet ouvrage collectif rassemble les contributions de professeurs et de doctorants du laboratoire GRISQ (Groupe de recherche sur l’information et la surveillance au quotidien) au sein de l’Universite du Quebec a Montreal, avec les contributions complementaires de deux chercheurs du domaine. Il repose sur un ancrage clair et affirme en recherche universitaire, alors que ces thematiques sont souvent investies par des auteurs proches de la consultance. La dimension collective de l’ouvrage est man...

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)0.005
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.079
Threshold uncertainty score0.157

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.014
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0030.002
Scholarly communication0.0090.010
Open science0.0010.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0230.013

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 head0.549
GPT teacher head0.401
Teacher spread0.147 · 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 designTheoretical or conceptual
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
Published2021
Admission routes2
Has abstractyes

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