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Record W2977742882 · doi:10.3917/pouv.170.0033

IA et emploi : une menace artificielle

2019· article· fr· W2977742882 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.

Bibliographic record

VenuePouvoirs · 2019
Typearticle
Languagefr
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsCanada Auto Workers
Fundersnot available
KeywordsHumanitiesSociologyPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

Les récents succès de l’ ia ont nourri un discours, souvent anxiogène, d’une obsolescence du travail humain. Si des acteurs divers ont intérêt à diffuser ce message, notre analyse d’informaticien et d’économiste, nécessairement spéculative, souligne les limites technologiques et sociales de l’intelligence artificielle. Nous renversons ainsi la problématique : l’ ia couplée aux robots sera-t-elle suffisante pour permettre aux sociétés occidentales fermées à l’immigration de répondre aux défis du xxi e siècle qui exigeront beaucoup de travail ?

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.962
Threshold uncertainty score0.998

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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.014

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 head0.016
GPT teacher head0.280
Teacher spread0.264 · 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