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The political-cultural origins of CSR: An historical comparative perspective

2012· article· en· W2900575540 on OpenAlexaff
José Carlos Marques

Bibliographic record

VenueAcademy of Management Proceedings · 2012
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicCorporate Social Responsibility Reporting
Canadian institutionsMcGill University
Fundersnot available
KeywordsCorporate social responsibilityPoliticsCapitalismPerspective (graphical)Context (archaeology)IndustrialisationPolitical scienceSociologyPolitical economyPositive economicsEconomic systemSocial scienceEnvironmental ethicsPublic relationsEconomics

Abstract

fetched live from OpenAlex

Recent breakthroughs and possible impasses in the corporate social performance (CSP) and corporate social responsibility (CSR) literatures have established the need to broaden the boundaries of analysis to encompass institutional explanations for why corporations might engage in socially beneficial activities. Building on these insights this paper traces the development of contemporary notions of CSR from an historical, political culture perspective. I demonstrate how political culture has had profound effects on the pattern of industrialization, as well as the structure of social welfare and labor market institutions of various countries. Drawing on various literatures including varieties of capitalism, political economy, and comparative social policy, I highlight the importance of understanding the historical-institutional context of corporate social responsibility. I conclude by providing a preliminary exploration of the implications of my findings for CSR theory and current CSR initiatives at the global level.

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)0.003
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0060.024
Scholarly communication0.0080.006
Open science0.0010.003
Research integrity0.0010.003
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 head0.083
GPT teacher head0.341
Teacher spread0.257 · 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 designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

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