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Record W1674702521 · doi:10.3917/hori.002.0076

Promouvoir la mobilité sur le marché du travail

2006· article· fr· W1674702521 on OpenAlexaff
George Asseraf, Yves Chassard

Bibliographic record

VenueHorizons stratégiques · 2006
Typearticle
Languagefr
FieldSocial Sciences
TopicSocial Sciences and Governance
Canadian institutions123 Certification (Canada)
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophy

Abstract

fetched live from OpenAlex

<titre>R&#233;sum&#233;</titre>Cet article pr&#233;sente et prolonge un certain nombre de r&#233;flexions &#233;mises lors d&#8217;un colloque organis&#233; par le Centre d&#8217;analyse strat&#233;gique en juin 2006. Il s&#8217;articule en deux &#233;tapes. La premi&#232;re poursuit trois objectifs&#160;: i) cerner les caract&#233;ristiques de la mobilit&#233; professionnelle en France, par comparaison avec d&#8217;autres pays d&#233;velopp&#233;s&#160;; ii) &#233;valuer les besoins de renouvellement de la main-d&#8217;&#339;uvre dans le contexte du papy-boom et d&#8217;un maintien du trend actuel de croissance&#160;; iii) sp&#233;cifier les diff&#233;rentes sortes de tension susceptibles d&#8217;appara&#238;tre sur le march&#233; du travail, afin de d&#233;terminer le type de mobilit&#233; qui pourrait y pallier. La seconde &#233;tape examine trois dimensions essentielles de la mobilit&#233; professionnelle&#160;: i) la mobilit&#233; interne et les strat&#233;gies d&#8217;entreprise capables de la stimuler&#160;; ii) le r&#244;le des branches pour d&#233;velopper la mobilit&#233; externe, m&#234;me intersectorielle&#160;; iii) le r&#244;le des territoires qui constituent un cadre de r&#233;f&#233;rence primordial non seulement pour &#233;valuer les besoins de formation, mais surtout pour organiser des mobilit&#233;s qui permettent de rem&#233;dier aux difficult&#233;s de recrutement rencontr&#233;es par les entreprises.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.708
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 studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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.

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".

Quick stats

Citations2
Published2006
Admission routes1
Has abstractyes

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