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Record W393361372

Impact du wiki sur la performance des projets en technologies de l'information

2015· article· fr· W393361372 on OpenAlexaboutno aff
Damien Brochot

Bibliographic record

Venuenot available
Typearticle
Languagefr
FieldSocial Sciences
TopicWikis in Education and Collaboration
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical scienceHumanitiesLibrary scienceArtComputer science
DOInot available

Abstract

fetched live from OpenAlex

Un wiki est une plateforme de travail collaboratif et un espace de travail virtuel ou toutes les parties prenantes d'un projet peuvent interagir simultanement a travers les differentes tâches et phases du cycle de vie d'un projet. Bien que des etudes recentes demontrent qu'un wiki a un impact significatif sur la performance des projets, les resultats ne permettent pas de conclure si une utilisation plus ou moins etendue est associee a une performance plus ou moins bonne dans tous les projets. De plus, meme si une equipe utilise frequemment un wiki, il est possible que l'adoption de cet outil ait peu d'impact sur la performance, puisque la rigueur dans l'application des methodes de gestion varie d'un projet a un autre. Pour verifier ces deux hypotheses, nous evaluons l'impact de l'utilisation du wiki sur la performance des projets dans une organisation du secteur public, en particulier les projets en technologies de l'information (TI). Nous developpons un questionnaire bilingue (francais et anglais) administre via le portail web de l'organisation a toutes les parties prenantes (leaders, equipes, clients) des projets au sein de 12 directions generales et de 5 bureaux regionaux. Sur une population de 9 300 personnes travaillant a l'Agence du Revenu du Canada (ARC), nous recueillons les repondants qui ont fait usage d'un outil de collaboration issu des technologies du Web 2.0, nomme wiki, au cours du cycle de vie d'un projet. Ainsi, les reponses de 121 repondants ont ete validees apres les verifications manuelles de chaque questionnaire. [...] [resume partiel]

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.742
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.022
GPT teacher head0.325
Teacher spread0.304 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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