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Record W7001828347

Les changements démographiques et les mutations du marché du travail au Portugal dans la dernière décennie du XX siècle

2008· book-chapter· fr· W7001828347 on OpenAlexaboutno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2008
Typebook-chapter
Languagefr
FieldBusiness, Management and Accounting
TopicIntellectual Property and Patents
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationLimitingPublic policy
DOInot available

Abstract

fetched live from OpenAlex

La proportion des plus de soixante ans passera dans les pays développés de 21% en 2007 à 31% en 2050. Cet ouvrage rassemble les analyses et recommandations d’une vingtaine d’experts au sujet de l’évolution de la population active en Belgique, au Canada, en France, au Québec, en Italie, au Portugal, en Roumanie, en Suisse et en Europe en général. Dans une première partie, prospective, sont présentés les changements démographiques et leurs interactions avec les niveaux d’activité, à l’horizon 2050. Une attention particulière est portée à l’augmentation du nombre des inactifs , sur le vieillissement des actifs et les conséquences possibles sur la productivité de la main-d’oeuvre. La deuxième partie présente des recherches abordant des aspects spécifiques des changements des structures, à savoir leurs impacts sur les professions, la formation et le fonctionnement des ménages, les pénuries éventuelles de main-d’oeuvre ainsi que la croissance continue des transferts vers des personnes âgées via le financement public des retraites et l’augmentation des dépenses de santé.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.321

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.159
GPT teacher head0.335
Teacher spread0.176 · 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 designObservational
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

Citations0
Published2008
Admission routes1
Has abstractyes

Explore more

Same venuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)Same topicIntellectual Property and PatentsFrench-language works237,207