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The Corporate Social Responsibility Agenda

2009· book-chapter· en· W316870807 on OpenAlexaff
Andrew Crane, Abagail McWilliams, Dirk Matten, Jeremy Moon, Donald S. Siegel

Bibliographic record

VenueOxford University Press eBooks · 2009
Typebook-chapter
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsYork University
Fundersnot available
KeywordsCorporate social responsibilitySubject (documents)InstitutionalisationPolitical sciencePublic relationsCritical reflectionEngineering ethicsSociologyEngineeringLibrary sciencePedagogyLawComputer science

Abstract

fetched live from OpenAlex

Abstract Corporate social responsibility (CSR) has experienced a journey that is almost unique in the pantheon of ideas in the management literature. Its phenomenal rise to prominence in the 1990s and 2000s suggests that it is a relatively new area of academic research. This book seeks to offer such a critical reflection on some of the major debates that coalesce around the subject of CSR. Bringing together a range of voices from within, across, and around the management literature, this book is intended as an authoritative account available on the CSR literature as it stands today, from the world's leading scholars in the area. This introductory article provides an overview of CSR as a subject of academic inquiry, discusses the institutionalization of the CSR literature, and outlines the guiding principles adopted in assembling this book and selecting the contributors.

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)0.004
metaresearch head score (Gemma)0.005
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: Review · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0040.013
Scholarly communication0.0170.009
Open science0.0010.006
Research integrity0.0070.008
Insufficient payload (model declined to judge)0.0120.002

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 head0.063
GPT teacher head0.233
Teacher spread0.170 · 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
GenreReview

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

Citations198
Published2009
Admission routes1
Has abstractyes

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