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Record W2118420500 · doi:10.1068/c1246r

Lisbonizing versus Financializing Europe? The Lisbon Agenda and the (un)Making of the European Knowledge-Based Economy

2013· article· en· W2118420500 on OpenAlexaff
Kean Birch, Vlad Mykhnenko

Bibliographic record

VenueEnvironment and Planning C Government and Policy · 2013
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHousing, Finance, and Neoliberalism
Canadian institutionsYork University
FundersOxford Brookes University
KeywordsLisbon StrategyKnowledge economyEuropean unionFinancializationEconomyWork (physics)Political sciencePolitical economyEconomicsMarket economyEngineeringInternational trade

Abstract

fetched live from OpenAlex

The Lisbon Agenda was meant to make the European Union ‘the most dynamic and competitive knowledge-based economy (KBE) in the world’ by 2010. As that date has now come and gone, it is apt to ask whether the Lisbon Agenda achieved its objective. We engage with this very question by analyzing new empirical material on the supposed transition to a KBE. Theoretically, we problematize the very notion that EU policies promoted the emergence of a KBE by highlighting how the Lisbon Agenda was tied to the financialization of the European economy. Our findings illustrate the abject failure of the EU's decade-long strategy to foster a new economy and better employment opportunities. We show that the main winners of the EU's economic strategy have been the finance sector and those who work in it. In summary, we argue that, despite the earlier assurances of Bell and Drucker, it is not the scientist or engineer but the banker who has been empowered to command a higher price in the new world of the KBE.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.735
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.028
GPT teacher head0.213
Teacher spread0.185 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2013
Admission routes1
Has abstractyes

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