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Record W4411555902 · doi:10.7202/1118414ar

L’analyse d’affaires comme <i>lingua franca</i> de la gouvernance de l’information : faciliter le positionnement stratégique du professionnel de l’information

2025· article· fr· W4411555902 on OpenAlex

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueArchives · 2025
Typearticle
Languagefr
FieldArts and Humanities
TopicLinguistics and Discourse Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsHumanitiesLingua francaPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

L’implantation efficace d’une stratégie de gouvernance de l’information exige la collaboration de plusieurs domaines d’expertise dont ceux de la gestion du risque et de la conformité aux lois, les technologies et la sécurité informatique, la mesure de la performance et la reddition de comptes, la planification stratégique et, bien entendu, la gestion de l’information organisationnelle. Dans ce paysage complexe où les différents acteurs impliqués envisagent l’information en fonction de perspectives différentes, l’analyse d’affaires présente un ensemble de pratiques, techniques et compétences qui ont le potentiel d’agir comme lingua franca de la gouvernance informationnelle. Cet article offre une introduction au domaine de l’analyse d’affaires en examinant les concepts qui permettent d’harmoniser les perspectives relatives à la gestion de l’information organisationnelle. En dotant le professionnel de l’information d’un langage commun axé sur la valeur et la gestion des risques, l’analyse d’affaires contribue indéniablement à le positionner comme un leader stratégique de la gouvernance de l’information.

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 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 score0.808
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.250
Teacher spread0.240 · 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