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Record W2128955290 · doi:10.7202/016489ar

Legal Dimensions of International Framework Agreements in the Field of Corporate Social Responsibility

2007· article· en· W2128955290 on OpenAlexvenueno aff
André Sobczak

Bibliographic record

VenueRelations industrielles · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Labor and Employment Law
Canadian institutionsnot available
Fundersnot available
KeywordsNegotiationMultinational corporationBusinessCorporate social responsibilityValue (mathematics)Law and economicsProcess (computing)International tradeInternational lawIndustrial organizationAccountingLawPolitical scienceEconomicsFinance

Abstract

fetched live from OpenAlex

The aim of this article is to offer an in-depth analysis of the different legal aspects of international framework agreements (IFAs) negotiated between multinational companies and global union federations. Using examples from different agreements, the article shows the potential added value IFAs have in contributing to an effective social regulation within international groups and global supply chains that are today regulated insufficiently by national, European and international labour law standards. It also analyses the impact of the international negotiation process of the IFAs and the powers of the signatory parties on the legally binding character of these texts. To conclude, the article discusses the potential added value of an optional legal framework for IFAs.

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)0.029
metaresearch head score (Gemma)0.029
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: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.154

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.029
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0090.057
Scholarly communication0.0140.017
Open science0.0020.007
Research integrity0.0070.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.050
GPT teacher head0.366
Teacher spread0.315 · 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
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

Citations58
Published2007
Admission routes1
Has abstractyes

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