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Record W4304136456 · doi:10.1111/rego.12501

From voluntary to mandatory corporate accountability: The politics of the German Supply Chain Due Diligence Act

2022· article· en· W4304136456 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRegulation & Governance · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicPolitical Influence and Corporate Strategies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsAccountabilityDue diligencePoliticsParliamentLegitimacyGermanBusinessSupply chainAgency (philosophy)AccountingCorporate social responsibilityBenchmarkingWindow of opportunityPublic relationsPublic administrationEconomicsPolitical scienceLawFinanceMarketingSociology

Abstract

fetched live from OpenAlex

Abstract Following a long‐standing and highly contested policy debate, in June 2021, the German parliament passed the Supply Chain Due Diligence Act requiring mandatory due diligence (MDD) of large companies, holding them accountable for the impacts of their supply chain operations abroad. Applying the discursive agency approach and using evidence from policy documents and 21 interviews with key stakeholders, we analyze the political strategies that paved the way toward MDD in Germany. The decisive strategy was an innovative benchmarking and monitoring mechanism that provided the legitimacy for a law and opened a window of opportunity for MDD supporters. Civil society and supportive politicians used this window of opportunity to build broad political coalitions that included the support of some companies. We discuss the ramifications of these findings for understanding the domestic politics behind the newly emerging norm of foreign corporate accountability.

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.610
Threshold uncertainty score0.856

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.023
GPT teacher head0.239
Teacher spread0.216 · 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