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Record W3112122969 · doi:10.1017/9781108781015.002

Explaining Public Interventions in Private Governance

2020· book-chapter· en· W3112122969 on OpenAlexaff
Stefan Renckens

Bibliographic record

VenueCambridge University Press eBooks · 2020
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicRegulation and Compliance Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCorporate governanceBusinessPublic goodCredibilityPublic economicsContext (archaeology)Private goodEconomicsPolitical scienceFinanceMicroeconomicsLaw

Abstract

fetched live from OpenAlex

The chapter develops a theory of public intervention in private governance. It examines the conditions under which a public authority will intervene and the form this intervention will take: standards and/or procedural regulations or the absence of intervention. The chapter explains that the type of public intervention depends on the interplay of two variables: the domestic benefits of product differentiation and the fragmentation of the private governance market. On the one hand, a pubic authority may intervene in the market for sustainably certified goods to improve the competitive position of domestic producers, who are the main rule targets of private governance schemes. On the other hand, a public authority can intervene to structure a fragmented private governance market in order to overcome problems such as supply chain confusion, a lack of credibility of existing private governance schemes, and trade and competitive distortions. The chapter further conceptualizes private governance schemes as interest groups that engage in lobbying. It also explains the dynamics of the theory in the context of the EU policymaking process and how the interventions may evolve over time.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.976
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.072
GPT teacher head0.217
Teacher spread0.145 · 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 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
Published2020
Admission routes1
Has abstractyes

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