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Record W7135476405

Ever-Growing Restrictions on Whom Public Buyers Can Contract with – Contemporary Developments in the EU Public Procurement

2023· other· en· W7135476405 on OpenAlexaff
Marta Andhov, Michal Andrzej Kania

Bibliographic record

VenueResearch at the University of Copenhagen (University of Copenhagen) · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsInstitute on Governance
Fundersnot available
KeywordsProcurementDirectiveSanctionsContext (archaeology)Subsidy
DOInot available

Abstract

fetched live from OpenAlex

This blog examines the ever-growing catalogue of restrictions on who can participate in the EU public procurement market and, consequently, with whom the public buyer (the contracting authority) cannot contract. We start by showcasing how freedom of contracting – one of the fundamental principles of contract law – is limited in the context of public procurement (section 1). Next, we look outside of EU Public Procurement Directives to sources of additional restrictions. These represent a clear reaction to contemporary challenges and include Sanctions Against Russia (section 2), Foreign Subsidies Regulation and International Procurement Instrument (section 3), Deforestation-Free Products Regulation and the Proposal for an Anti-Greenwashing Directive (section 4). Finally, we provide some conclusions.

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)0.011
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.012
Threshold uncertainty score0.059

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.011
Scholarly communication0.0120.009
Open science0.0010.006
Research integrity0.0040.004
Insufficient payload (model declined to judge)0.0100.001

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 head0.140
GPT teacher head0.292
Teacher spread0.152 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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