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Record W4235964086 · doi:10.22215/rera.v10i1.263

The Slow Road to the Social Investment Perspective in the European Union

2016· article· en· W4235964086 on OpenAlexaffvenue
Shannon Dinan

Bibliographic record

VenueReview of European and Russian Affairs · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsUniversité de MontréalCarleton University
Fundersnot available
KeywordsEuropean unionInvestment (military)Social protectionPolitical scienceLisbon StrategyPopulationSocial policySocial positionSocial exclusionPovertyEconomic growthLegislatureSocial economySocial changeEconomicsSociologyEconomic policyPoliticsLaw

Abstract

fetched live from OpenAlex

The European Union has no unilateral legislative capacity in the area of social policy. However, the European Commission does play the role of guide by providing a discursive framework and targets for its 28 Member States to meet. Since the late 1990’s, the EU’s ideas on social policy have moved away from the traditional social protection model towards promoting social inclusion, labour activation and investing in children. These new policies represent the social investment perspective, which advocates preparing the population for a knowledge-based economy to increase economic growth and job creation and to break the intergenerational transmission of poverty. The EU began the gradual incorporation of the social investment perspective to its social dimension with the adoption of ten-year strategies. Since 2000, it has continued to set goals and benchmarks as well as offer a forum for Member States to coordinate their social initiatives. Drawing on a series of interviews conducted during a research experience in Brussels as well as official documents, this paper is a descriptive analysis of the recent modifications to the EU’s social dimension. It focuses on the changes created by the Europe 2020 Strategy and the Social Investment Package. By tracing the genesis and evolution of these initiatives, the author identifies four obstacles to social investment in the European Union's social dimension.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.813
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.025
GPT teacher head0.323
Teacher spread0.297 · 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 designTheoretical or conceptual
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
Published2016
Admission routes2
Has abstractyes

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