MétaCan
Menu
Back to cohort
Record W4211138078 · doi:10.3917/pox.134.0007

La réforme, le chiffrage, son modèle et ses données

2022· article· fr· W4211138078 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

VenuePolitix · 2022
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutionsMusée de la Civilisation
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

L’article retrace le processus par lequel la microsimulation, nouvelle forme d’évaluation ex ante , s’est imposée comme l’instrument privilégié pour concevoir et anticiper des effets d’une réforme du système socio-fiscal en France. Principalement conçus au sein des administrations « chiffreuses », les modèles de microsimulation sont d’abord élaborés de façon non coordonnée, appelant des jeux de concurrence mais aussi de coopération entre les équipes et institutions en charge de leur développement. Une nouvelle étape s’amorce à la fin des années 2000. Le monopole quasi exclusif de l’administration sur la microsimulation s’érode avec le retour progressif des économistes académiques dans le domaine. En découle une recomposition du paysage de la microsimulation qui, malgré la subsistance d’entreprises concurrentes, affirme un monopole de l’instrument sur la façon de penser une réforme du système socio-fiscal.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
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 score0.849
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.058
GPT teacher head0.317
Teacher spread0.259 · 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