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Corporate Social Responsibility and Government

2010· book-chapter· en· W290935236 on OpenAlexaff
Jeremy Moon, Nahee Kang, Jean‐Pascal Gond

Bibliographic record

VenueOxford University Press eBooks · 2010
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsHEC Montréal
FundersEconomic and Social Research Council
KeywordsCorporate social responsibilityGovernment (linguistics)Corporate governanceContext (archaeology)CapitalismPoliticsPolitical scienceRelation (database)State (computer science)Political economyEconomyEconomic systemSociologyPublic relationsEconomicsManagementGeographyLaw

Abstract

fetched live from OpenAlex

Abstract This article is about corporate social responsibility (CSR) and aims to distinguish different types of CSR–government relationship and to understand these in the context of broader state roles and government–business relations. It investigates these relationships comparatively, historically, and in terms of new institutionalism. It does so comparatively by investigating CSR and government in four types of political system on the assumption that CSR reflects features of respective national business systems, or varieties of capitalism, in which government roles are critical. Thus it considers CSR in the USA, in Europe, in the transitional economies of East Asia, Eastern Europe, and South Africa, and globally. The article's special focus on the USA is justified because, although business responsibilities have long existed throughout the world, in America the concept of CSR emerged as a basis for reflection on its relation to the wider purpose of the firm in the context of institutions of governance.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.006
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.010
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.040
GPT teacher head0.209
Teacher spread0.169 · 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 designTheoretical or conceptual
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

Citations31
Published2010
Admission routes1
Has abstractyes

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