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Record W4405365132 · doi:10.1522/radm.no8.1833

Éditorial

2024· article· fr· W4405365132 on OpenAlexaffvenue
Éric Jean

Bibliographic record

VenueAd machina l avenir de l humain au travail · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicMulticulturalism, Politics, Migration, Gender
Canadian institutionsUniversité du Québec à Chicoutimi
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

Les transformations organisationnelles : un progrès?Ce numéro thématique de la revue Ad Machina s'intéresse aux effets positifs des diverses transformations organisationnelles ainsi qu'aux défis qu'entrainent ces changements.En effet, les organisations traversent une époque marquée par des mutations profondes, catalysées par des avancées technologiques, des bouleversements sociaux et des évolutions culturelles.Ces transformations, qu'elles soient choisies ou imposées, suscitent un questionnement majeur : jusqu'à quel point les transformations organisationnelles peuvent-elles être considérées comme un progrès ?Avec ce huitième numéro, la revue Ad machina propose d'explorer ce questionnement crucial sous des perspectives variées, croisant analyses empiriques, théoriques et critiques.Dans ce numéro, divers auteurs explorent les thématiques suivantes :

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)0.002
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.240
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.013
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0020.001
Scholarly communication0.0070.004
Open science0.0020.002
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.2400.118

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 head0.068
GPT teacher head0.381
Teacher spread0.313 · 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 designNot applicable
Domainnot available
GenreEditorial

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
Published2024
Admission routes2
Has abstractyes

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